Informatics Focus - European Pharmaceutical Review · grown systems got bigger, demonstrating the capability and commercial potential, and acting as a precursor to the Laboratory

www.europeanpharmaceuticalreview.com Issue 4 2014

Informatics FocusWith articles from Brittany Melton from the University of Kansas

and John Trigg from phaseFour Informatics

ProteinexpressionMarco Casteleijn and DominiqueRichardson from the University of Helsinkiexplore engineering cells and proteins

NIR FocusMonitoring pharmaceutical powder

mixing by NIR spectroscopy, plus a look into moving towards

continuous manufacturing withNIRS and NIR-CI systems

www.bmglabtech.com

Microplate reader with revolutionary LVF MonochromatorTM technology

Fluorescence, Fluorescence Polarization, TRF, TR-FRET/HTRF®,

Luminescence, AlphaTechnology, and Absorbance

Discover the most sensitive monochromator-based microplate reader.

CLARIOstar® - Any Wavelength. Any Bandwidth. Any Assay.

Monochromator. Reinvented!

Visit us at ELRIG 2014 in Manchester.

VOLUME 19 ISSUE 4 2014 European Pharmaceutical Review 1

INTRODUCTION

European Pharmaceutical Review is proud to be affiliated with JPAG (Joint Pharmaceutical Analysis Group), a not-for-profit organisation for pharmaceutical analysts. Free subscriptions are available for members of JPAG.

Please contact Karen Hutchinson [email protected] for further details.

Registered Office as above.Russell Publishing Ltd, is registered as a Limited Company in England, Number 2709148VAT Number GB 577 8978 47

Follow us on Twitter:http://twitter.com/PharmaReview

No responsibility can be accepted by Russell Publishing Limited, the editor, staff or any contributors for action taken as a result of the information and other materials contained in our publications. Readers should take specific advice whendealing with specific situations. In addition, the views expressed in our publi cations by any contributor are not necessarily those of the editor, staff or Russell Publishing Ltd. As such, our publications are not intended to amount to advice onwhich reliance should be placed. We therefore disclaim all liability and responsibility arising from any reliance placed on such materials by any reader, or by anyone who may be informed of any of its contents. Published August 2014

Independent auditwatchdog service forprinted publications

European Pharmaceutical Review can guarantee its circulation is 11,999 (for the 6 issues distributed between 1 January and 31 December 2013). The publication is ABC audited.This is an independent verification that our circulation is genuine.

Join us on LinkedIn:http://linkd.in/PharmaReview

EDITORIAL BOARDSheraz GulVice President and Head of Biology, European ScreeningPort GmbHMatthew MoranDirector, PharmaChemical IrelandDon ClarkPfizer Global Research & DevelopmentMichael J. MillerPresident, Microbiology ConsultantsMichael H. ElliottCEO, Atrium Research & ConsultingDavid ElderDirector Externalisation Group, GlaxoSmithKlineAndrew TeasdalePrincipal Scientist – Chair of Impurities Advisory Group, AstraZeneca

RUSSELL PUBLISHING LTD Founder: Ian RussellManaging Director: Josh RussellEditorial Manager: Craig WatersDeputy Editor: Annie McKennaSenior Publications Assistant: Karen HutchinsonGroup Sales Director: Tim DeanPublisher: Freddy WhiteSenior Sales Executive: Andrew JohnsonProduction Manager: Brian ClokeFront Cover Artwork: Steve Crisp

European Pharmaceutical Review (ISSN No: 1360-8606, USPS No: 023-422) is published bi-monthly by Russell Publishing Ltd, GBR and distributed in the USA by Asendia, 17B S Middlesex Ave, Monroe NJ 08831. Periodicals postage paid New Brunswick, NJ and additional mailing offices.POSTMASTER: send address changes to European PharmaceuticalReview, 701C Ashland Ave, Folcroft PA 19032.

European Pharmaceutical Review is published bi-monthly (six times per annum) and is available by subscription at £90.00 for a year, which includes on-line membership access. Back issue copies can be requested at £15.00 per copy.

European Pharmaceutical Review: Published by Russell Publishing Ltd, Court Lodge, Hogtrough Hill, Brasted, Kent, TN16 1NU, UK Tel: +44 (0) 1959 563311 Fax: +44 (0) 1959 563123 Email: [email protected]

ISSN 1360 - 8606Copyright rests with the publishers.All rights reserved©2014 Russell Publishing Limited

Welcome to the fourth issue this year of European Pharmaceutical Review.As with previous editions of our publication, we bring another two informative In-Depth

Focus sections to you in this issue – a section that has become popular among our readersand allows us to group together two or three articles that focus on one particular area of thepharmaceutical industry. In this edition we bring you Informatics (page 27) and NIR (page 49).

Informatics is a topic under the spotlight in many industries, and the impact of digitaltechnologies has been remarkable in some realms. In the pharmaceutical world, “the pace ofdigital change has been relatively leisurely,” writes John Trigg from phaseFour Informatics(page 33). John explains that it has taken around four decades to reach a point where anincreasing number of laboratories can consider themselves to be electronic or paperless. Heexplores the notion that as the power of computer technology developed, interestprogressively turned towards managing and collating laboratory data, and numerous home-grown systems got bigger, demonstrating the capability and commercial potential, and acting as a precursor to the Laboratory Information Management Systems (LIMS) industry.John brings his informative article to a close by writing, “Ideally, the use of laboratoryinformatics tools should not be perceived as an intrusive bureaucratic process, butsomething that facilitates the scientific method and doesn’t intrude on the social andintellectual processes that are essential to the science.”

Over in the world of near-infrared (NIR) spectroscopy, Lizbeth Martinez from NovartisSwitzerland (page 57) focuses on how it is a technology that has attracted a lot of attention from the pharmaceutical world as well as health authorities. Lizbeth explains, “NIR spectroscopy can measure bulk samples without any preceding treatment, thus makingit a very appealing technology for the real-time monitoring of pharmaceutical processes.” In summary of her informative article, Lizbeth states, “NIR spectroscopy is increasinglybecoming a common tool for process monitoring and control, which leads to the betterunderstanding and improvement of the mixing processes.”

Other topics featured within this edition include protein expression (page 12), particlesizing (page 37) and X-Ray Fluorescence (page 62).

We also preview two forthcoming Webinars, both hosted by European PharmaceuticalReview – turn to pages 56 and 61 to learn more.

If you would like to contribute to a future issue of European Pharmaceutical Reviewwith a by-lined article or an informative news item, please contact us via email at [email protected]. Please also bookmark our website atwww.europeanpharmaceuticalreview.com where you can find details of current and futureissues, sector news and event details. Don’t forget you can also join our groups on LinkedInand Twitter – details are opposite.

Freddy WhitePublisher, European Pharmaceutical Review

Focusing onInformatics and NIR…

We’ve Been There

Pharma&Biotech

QC Tests from People Who Use Them

We’ve walked in your shoes and know the challenges you face in a regulated, manufacturing environment. As a manufacturer ourselves, we face them too. Our decades of experience are part of every QC Testing product and service we offer. We know your business depends on the quality and reliability of your testing products – that’s why we build them that way.

Our portfolio includes: – Endotoxin Detection products, services and industry-leading

software – MODA™ QC Micro: Paperless, mobile and flexible sampling and

data collection QC Testing Solutions – transforming practical knowledge into action.

www.lonza.com/qc© 2014 Lonza Walkersville, Inc.

1 INTRODUCTIONFocusing on Informatics and NIR…Freddy White, Publisher, European Pharmaceutical Review

5 FOREWORDCan HPLC assay methods really be considered quality critical tests?David Elder, GlaxoSmithKline and JPAG

6 EVENTS

8 NEWS

12 PROTEIN EXPRESSIONEngineering cells and proteins – creating pharmaceuticalsMarco Casteleijn and Dominique Richardson, University of Helsinki

21 MULTIVARIATE DATA ANALYSISThe flexibility of regularisationprocesses for multivariate calibration maintenanceJohn H. Kalivas, Idaho State University

25 SHOW PREVIEWDrug Discovery 2014

27 IN-DEPTH FOCUS: INFORMATICSFeaturing articles from Brittany Melton at the University of Kansas (page 29) and John Trigg from phaseFour Informatics (page 32).

37 PARTICLE SIZINGParticle characterisation in drug deliveryDriton Vllasaliu and Ishwar Singh, University of Lincoln

42 LEAN MANUFACTURINGLean, Six Sigma, people and organisationsStephen McGrath, Teva Pharmaceuticals Ireland (TPI)

47 SHOW PREVIEW:MipTec 2014

49 IN-DEPTH FOCUS: NIRFeaturing articles from José Manuel Amigo at the Department of Food Science from the University of Copenhagen,Milad Rouhi Khorasani and Jukka Rantanen from the Departmentof Pharmacy at the University of Copenhagen, Poul Bertelsenfrom Tekada Pharma A/S (page 51), and Lizbeth Martinez fromNovartis Switzerland (page 57).

62 X-RAY FLUORESCENCENovel methodologies for determining the mineral content of complex multivitamin tabletsRyan Gosselin, Nicolas Abatzoglou and Philip Quinn (Process Analytical Sciences Group, Pfizer Canada), at the Pfizer Industrial Research Chair from the University ofSherbrooke, Joanny Salvas and Jean-Sébastien Simard from the Process Analytical Sciences Group at Pfizer Canada

69 SHOW PREVIEWCPhI Worldwide 2014

72 PRODUCT HUBBD

Contents


COMING UP IN THE NEXT ISSUE:• Rapid Micro Methods Focus• Flow Cytometry

• Spray Drying• Protein Characterisation

Published October 2014. Don’t miss out on your copy by subscribing today. Visit www.europeanpharmaceuticalreview.com or contact Karen Hutchinson

via email at [email protected].

With the largest network of harmonized bio/pharmaceutical

GMP product testing labs worldwide, Eurofins BioPharma

Product Testing is everywhere you are.

While delivering a true local lab experience, our

international presence ensures personal quality service

backed by a unique global breadth of harmonized

capabilities to solve all your testing challenges.

For the most complete range of global testing services,

harmonized quality systems and LIMS, you’ll never need to

look further than your own backyard.

Chemistry/Biochemistry

Cell Banking Services

Facility & Process Validation

Method Development & Validation

Microbiology

Molecular & Cell Biology

Raw Materials Testing

Release Testing

Residuals & Impurities Testing

Stability Testing & Storage

Viral Clearance & Viral Safety

Professional Scientific StaffingSM

Services

Belgium

Denmark

France

Germany

Ireland

Italy

Spain

Sweden

U.S.

Facilities

Right In Your Backyard.

The Largest Global

Footprint of Harmonized

Testing Labs...

www.eurofins.com/biopharma

BioPharmaProduct Testing

A method’s ability to rapidly identify significant changes in the truemean of an API (Active Pharmaceutical Ingredient) is essential for anyquality critical test. Hofer et al3 modelled a scenario where for the first50 batches of an API, the true mean was 99.5% and the standarddeviation (σ) was 0.5%; thereafter the true mean dropped to 99.0%,with unchanged σ. The modelling showed an inability to identify thissignificant change by trending the HPLC assay data. The authorsproposed the use of a mass balance approach (100% – % totalimpurities) demonstrating unequivocally that it is relativelystraightforward to detect changes using this approach.

The analytical methodology variability is frequently larger than themanufacturing process variability, particularly for API manufacture.Generally, the analytical method σ should be ≤one-sixth of theproposed specification range; i.e. 6σ capability. Ermer4 assessed the maximum allowable σ for an API assay method. He showed for anAPI assay method using duplicate determinations, where the lowerspecification limit is 98.0% and with 0.5% total impurities, that theanalytical method σ should be ≤0.17%. Ermer et al5 used 44 differentAPIs, and 156 different stability studies to determine a generic precisionvalue for HPLC assays, i.e. 1.1%6. Similarly, Hofer et al3 reported that themean intermediate precision values were between 0.6-1.1% and Görög7

indicated variability was about 1%. Based on this typical analytical variability of ca. 1%, and assuming

an API specification ranges of ±2.0% (i.e. 98.0-102.0%), severalcommentators3,4,5,7 have expressed significant concerns about the utilityof HPLC assay methods to monitor API quality (trending API potency,trending API stability, releasing batches whose true potency is 98.0-102.0% or meaningfully investigating OOS (Out of Specification) results).Skrdla et al8 indicated that ‘assay results are simply not stability-indicating’ because of the intrinsic assay variability. The impact ofmethod variability on OOS results is also constrained by the FDA’s 2006guidance, as individual replicates, as well as the mean value, should liewithin the acceptance criteria9. Hofer et al3 modelled the probability offinding a ‘false OOS’ and demonstrated that this is highly dependent onmethod variability, as well as the API true mean. They also reflected thatthere was a 1% chance of OOS results when the σ was 0.6%, with a true

mean of 99.4%, but this increased 9-fold when the σ increased to 1%,with an identical true mean. The possibility of seeing ‘false OOS’increases with the number of tests performed on the same batch, i.e. asin the case of routine stability testing3. This issue can be circumventedby registering broader API specifications based on process capability,but this requires regulatory endorsement.

Hofer et al3 assessed the potency data from eight API batches usingboth standard HPLC assay and the mass balance approach. Althoughthe mean assay data were similar, the precision of the former data wasabout 6-8 fold higher than the corresponding mass balance HPLC assayapproach. Skrdla et al8 proposed the complete removal of the externalstandard HPLC potency assays from routine use within stability studiesand advocated utilising the more precise mass balance HPLC assayapproach. Finally, method variability has an adverse impact on thepredicted shelf life of the API which can be addressed using an accurateand very precise analytical method10.

In conclusion, without some relaxation of the standard APIspecification limits (normally, 98.0-102.0%) the use of a standard HPLCassay to monitor API quality must be approached with caution due to itsinability to monitor quality critical changes.

Analytical method specificity is assessed using ICH (International Conference on Harmonisation) Q2 (2005)1.Although, certain methods are not specific enough for their intended purposes, they may have other advantages.Both titrimetric and UV (Ultra-violet spectroscopy) assays are non-specific, but have superior precision (ca. 0.1-0.5%RSD (Residual Standard Deviation)) compared with the corresponding specific HPLC (High Performance LiquidChromatography) assay methods (>0.5% RSD)2.

FOREWORD

Can HPLC assaymethods really beconsidered quality

critical tests?Dave ElderGlaxoSmithKline and JPAG


1. ICH Q2 (R1). 2005. Validation of analytical procedures: Text and methodology.http://www.ich.org/fileadmin/Public_Web_Site/ICH_Products/Guidelines/Quality/Q2_R1/Step4/Q2_R1__Guideline.pdf. Accessed on 28th March 2014.

2. Dejaegher B., et al. 2006. Improving method capability of a drug substance HPLC assay. J. Pharm. Biomed. Anal. 42: 155-170.

3. Hofer J.D., et al. 2007. Is HPLC assay for drug substance a useful quality control attribute? J. Pharm. Biomed. Anal. 44: 906-913.

4. Ermer J. 2001. Validation in pharmaceutical analysis. Part I: An integrated approach. J. Pharm.Biomed. Anal. 24: 755-767.

5. Ermer J., et al. 2005a. Precision from drug stability studies. Investigation of reliable repeatabilityand intermediate precision of HPLC assay procedures. J. Pharm. Biomed. Anal. 38: 653-663.

6. Ermer J., et al. 2005b. Validation in pharmaceutical analysis Part II: Central importance ofprecision to establish acceptance criteria and for verifying and improving the quality of analyticaldata. J. Pharm. Biomed. Anal. 37: 859-870.

7. Gorög S. 2005. The sacred cow: the questionable role of assay methods in characterising thequality of bulk pharmaceuticals. J. Pharm. Biomed. Anal. 36: 931-937.

8. Skrdla P.J., et al. 2009. Use of a quality-by-design approach to justify the removal of the HPLC weight % assay from routine API stability testing protocols. J. Pharm. Biomed. Anal. 50: 794-796.

9. FDA. 2006. Guidance for industry: investigating Out-of-Specification (OOS) results forpharmaceutical production. US department of health and human services, Food and DrugAdministration, CDER.

10. Magari R.T. Uncertainty of measurement and error in stability studies. J. Pharm. Biomed. Anal. 45: 171-175.

References

SEPTEMBER 2014ELRIG Drug Discovery 2014Date: 2 – 3 September 2014Location: Manchester, UKe: [email protected]: http://elrig.org/portfolio/drug-discovery-2014/

Royal PharmaceuticalSociety Annual Conference 2014Date: 7 – 8 September 2014Location: Birmingham, UKe: [email protected]: http://www.rpharms.com/rps-annual-conference/rps-conference-2014.asp

50th Congress of theEuropean Societies of ToxicologyDate: 7 – 10 September 2014Location: Edinburgh, Scotlande: [email protected]: www.eurtox2014.com

Global PharmaManufacturing SummitDate: 8- 9 September 2014Location: Boston, MA, USAe: [email protected]: http://gpmsummit.com

15th InternationalConference on Alzheimer’sDrug DiscoveryDate: 8 – 9 September 2014Location: Jersey City, NJ, USAe: [email protected]: www.worldeventsforum.com/adff/addrugdiscovery

PharmaTech Africa Exhibition & ConferenceDate: 9 – 11 September 2014Location: Accra, Ghanae [email protected]: http://pharmatechafrica.com

GCC PharmaceuticalCongressDate: 14 – 17 September 2014Location: Dubaie: [email protected]: http://gccpharmacongress.com/

Lab-on-a-Chip &Microarray WorldCongressDate: 18 – 19 September 2014Location: San Diego, USAe: [email protected]: http: //selectbiosciences.com/conferences/index.aspx?conf-LOACW2014

12th Annual Pharma ITCongress 2014Date: 22 – 23 September Location: London, UKe: [email protected]: http://www.pharmatechnology-summit.com/download-agenda-marketing/

Quality by DesignDate: 22 – 24 SeptemberLocation: Vienna, Austriae: [email protected]: http://atnd.it/12211-0

EUSTM-2014Date: 22 – 25 September 2014Location: Vienna, Austriae: [email protected]: www.eutranslationalmedicine.org/eustm-2014

8th Annual EuropeanMedical Information &CommunicationsConferenceDate: 23 September 2014Location: London, UKe: [email protected]: http://atnd.it/7423-1

MipTecDate: 23 – 25 September 2014Location: Basel, Switzerlandw: www.miptec.com

Microbiology & Infectious Diseases CongressDate: 29 – 30 September 2014Location: London, UKe: [email protected]: http://www.microbiology-congress.com/download-agenda-marketing/

5th Annual Biosimilars & BiobettersDate: 29 – 30 September 2014Location: London, UKw: www.smi-online.co.uk/2014biosimilars76.asp

TechnoPharm 2014Date: 30 September – 2 OctoberLocation: Nurnberg, Germanyt: +49 (0) 9 11.86 06-83 55w: www.technopharm.de

OCTOBERCell Culture &BioProcessing ForumDate: 1 – 2 October 2014Location: Berlin, Germanye: [email protected]: http://pharma.flemingeurope.com

Antibody EngineeringSeminarDate: 2 October 2014Location: London, UKe: [email protected]: http://www.oxfordglobaltraining.com/about-us/antibody-engineering/

Formulation & DrugDelivery CongressDate: 2 – 3 October 2014Location: London, UKe: [email protected]: www.formulation-congress.com

HUPO 2014Date: 5 – 8 October 2014Location: Madrid, Spaine: [email protected]: http://www.hupo2014.com/

Antibody Drug Conjugates SeminarDate: 6 October 2014Location: Oxford, UKe: [email protected]: http://www.oxfordglobaltraining.com/about-us/antibody-drug-conjugates/

CPHi Worldwide 2014Date: 7 – 9 October 2014Location: Paris, Francee: [email protected]: www.cphi.com/Europe/home

How Similar MustBiosimilars Be?Date: 16 October 2014Location: London, UKe: [email protected]: www.jpag.org/?p=meetings&r=47

NOVEMBER6th World Congress onDiabetes & MetabolismDate: 3 – 5 November 2014Location: Las Vegas, USAe: [email protected]: www.omicsgroup.com/diabetes-metabolism-conference-2014

DECEMBERStability Challenges Part II: Assuring theStability of Medicines from Manufacture toClinical UseDate: 11 December 2014Location: London, UKE: [email protected]: www.jpag.org/?p=meetings&r=54

PHARMA EVENTS

6 European Pharmaceutical Review VOLUME 19 ISSUE 4 2014

If you have a diary event youwish to publicise, send details to:[email protected]

UPLC® technology for your lab. Competitive advantage for you. With best-in-class UPLC separations in a range of chromatography modes: Reversed phase (RP), ion exchange (IEX), size exclusion (SEC), and hydrophilic interaction (HILIC). Extract more information from a separation. Know more about your biomolecule. Leave your competition behind. Learn more at waters.com/hclassbio

Your new biopharm system will run a full range of chromatography modes and all applications. Your competition will run for cover.

©2014 Waters Corporation. Waters, UPLC, ACQUITY UPLC and The Science of What’s Possible are registered trademarks of Waters Corporation.

BIO SYSTEM[ ]ACQUITY UPLC H-CLASS

NEWS: PEOPLE

8 European Pharmaceutical Review VOLUME 19 ISSUE 4 2014 Catch up with daily news at www.europeanpharmaceuticalreview.com

BIOGEN IDEC

Biogen Idec names Adriana Karaboutis EVP,Technology and Business SolutionsBiogen Idec recently announced the appointment of Adriana (Andi) Karaboutis as Executive VicePresident of Technology and Business Solutions, effective 24 September 2014. She will reportdirectly to the company’s Chief Executive Officer, George Scangos, Ph.D., and will be a memberof the Biogen Idec management team.

Andi will lead Biogen Idec’s information technology (IT) operations and advance thecompany’s use of technology and data to enhance overall engagement with patients and healthcareproviders. In this new role, she will drive technology initiatives throughout the entire organisation,leading Biogen Idec’s efforts to leverage advanced analytics to inform the drug discovery process,unlock new insights from clinical data and improve patient care through tools such as wearable andingestible devices.

“Andi is a remarkable technology leader who will enable Biogen Idec to infuse digitalinnovation at all levels of our business and research organisations,” said Dr. Scangos. “As the paceof digital innovation accelerates, Andi will play a critical role in our mission to improve humanhealth and support those who serve patients. She views data and information as a new currency togain insights, tailor conversations, improve research and achieve business goals.”

Andi joins Biogen Idec from Dell where she was Vice President and Chief Information Officerwith responsibility for the company’s overall IT enterprise and customer experience. Herbackground also includes leadership roles in global IT and business operations at Ford MotorCompany and General Motors.

Andi received a bachelor’s of science in Computer Science as a Merit Scholar from WayneState University and has completed the accelerated Marketing Strategy Program at DukeUniversity’s Fuqua School of Business.

www.biogenidec.com

AMGEN

Amgen names Elliott M. Levy, M.D., Senior Vice President, Global DevelopmentAmgen announced recently that Elliott M. Levy,M.D., has been named Senior Vice President ofGlobal Development, effective 8 September2014. Elliott comes to Amgen from Bristol-Myers Squibb (BMS), where he most recentlyserved as Senior Vice President and Head ofSpecialty Development.

“Elliott brings a wealth of development and leadership experience to his new role atAmgen,” said Sean E. Harper, M.D., Execu-tive Vice President of Research andDevelopment at Amgen. “His track record shows his success in leading major clinicaldevelopment programs, and we’re confident thathe will help Amgen to serve patients byadvancing the large number of potential newmedicines in our late-stage pipeline.”

In his 17-year career at BMS, Elliott servedin a range of senior positions spanning the

spectrum of clinical development and relatedresponsibilities. Prior to his current role, Elliottled Global Pharmacovigilance and Epi -demiology at BMS. Other previous rolesincluded Cardiovascular Clinical Development,Immunoscience Clinical Research, and GlobalClinical Research Operations.

Elliott is a graduate of Yale College andSchool of Medicine, where he was Chief MedicalResident and trained in Internal Medicine andNephrology. He completed fellowship training inclinical research through the Robert WoodJohnson Clinical Scholars programme. Beforejoining BMS, he was a member of the RenalDivision at Brigham and Women’s Hospital in Boston, where he was an investigator infederally-sponsored outcomes research as well asindustry-sponsored clinical trials.

www.amgen.com

MIDATECH

Midatech appoints Nick Robbins-Cherry asFinance DirectorMidatech Ltd. – a global leader in the design,synthesis and manufacture of nanomedicinesbased on its unique gold glycan coatednanoparticle (GNP) technology – is pleased toannounce that Nick Robbins-Cherry MBA ACAhas been appointed as Finance Director, furtherstrengthening the company’s senior manage-ment team.

Nick is a chartered accountant with over 15 years of experience in senior commercial andfinance roles and a proven track record in mergersand acquisitions (M&A). He joins Midatech fromThe Marketing Practice, one of the UK’s leadingbusiness-to-business marketing agencies, wherehe acted as Finance and Commercial Directorsince January 2013. Prior to that, Nick spent fiveyears at CACI, the UK subsidiary of CACIInternational Inc., the NYSE quoted provider ofmarketing solutions and IT systems, as M&AManager and then Finance Director where he hadoverall responsibility for M&A activity.

Nick joined CACI from Invocom, aprovider of technical consultancy services to thetelecommunications industry, where he held theposition of Finance Director from 2001 until thebusiness was successfully acquired by CACI inJanuary 2008. Nick has also held senior financialpositions at LifeGard Technologies, Janssen-Cilag and ICI.

Commenting on the appointment, Dr JimPhillips, CEO of Midatech, said: “I am delightedto welcome Nick to the company as our newFinance Director. Nick’s experience in seniorcommercial and finance roles and his trackrecord of M&A will prove invaluable toMidatech as we look to expand the company andcommercialise novel therapeutics based on ourgold nanoparticle technology.”

Nick added: “I am excited to be joiningMidatech and to have the opportunity to helpdrive forward the commercialisation of its game-changing GNP technology. I have been hugelyimpressed by the potential of this technology forthe targeted delivery of therapeutics to tumourcells and for the treatment of diabetes and I amconfident that Midatech has the managementteam in place to deliver significant growth andvalue in the coming years.”

www.midatechgroup.com

NDA PARTNERS

NDA Partners welcomes Agnes Westelinck as a Premier Expert ConsultantNDA Partners LLC has announced that Agnes Westelinck, PharmD, hasjoined the firm as a Premier Expert Consultant. NDA Partners PremierExperts are top-tier consultants whose expertise and professional statureenable them to bring extraordinary value to the company’s clients.Premier Experts collaborate to design and implement critical solutions tohelp clients successfully develop their medical products, pursue optimalregulatory pathways, build companies that are attractive to professionalinvestors, and initiate access to global markets.

Agnes is a highly regarded pharmaceutical industry senior executivewith significant experience in the development and regulatory approval ofdrugs in the U.S., EU and Asia. She was formerly Executive Director and

Global Head of Regulatory Affairs, Oncology, for GlaxoSmithKline,Director of Regulatory Affairs at Hoffman-La Roche, and VisitingScientist/Executive at the U.S. Food & Drug Administration (FDA),Office of Drug Evaluation, Division of Oncology (CDER).

In addition to global product development and regulatory strategy, Agnes’ expertise includes innovative approaches in drug development and emerging. She also provides strategic input for portfolio and licensing/deal-making decisions, and guidance forIND and NDA submissions, rare diseases, biomarkers, and acceler-ated approvals.

www.ndapartners.com

Catch up with daily news at www.europeanpharmaceuticalreview.com VOLUME 19 ISSUE 4 2014 European Pharmaceutical Review 9

NEWS: EUROPE AT A GLANCE

ALCON

Alcon’s Simbrinza® approved in the EU to treatpatients living with glaucomaAlcon, the global leader in eye care and adivision of Novartis, announced thatSimbrinza® eye drops suspension (brinzola -mide 10mg/mL and brimonidine tartrate2mg/mL) has been approved by the EuropeanCommission to decrease elevated intraocularpressure (IOP) in adult patients with open-angle glaucoma or ocular hypertension, forwhich monotherapy provides insufficient IOP reduction1.

Simbrinza® combines two well-established treatments for elevated IOP intoone multi-dose bottle, offering a simplifiedschedule compared to brinzolamide andbrimonidine administered separately.Simbrinza® is also the only fixed-combinationglaucoma treatment without a beta-blocker.Beta blockers are commonly prescribed tolower IOP, but are contraindicated for manyglaucoma patients suffering from certainrespiratory or cardiac conditions2.

“Simbrinza® complements Alcon’sglaucoma portfolio by addressing a significantunmet patient need. We are pleased tointroduce the only fixed combination therapywithout a beta-blocker to help more glaucomapatients manage their progressive eyecondition,” said Jeff George, Global Head ofAlcon. “As the leader in eye care, Alcon willcontinue to invest in R&D to expand ourbroad portfolio of glaucoma treatment optionsand to further reduce the burden of this silent,sight-threatening disease.”

Glaucoma is a group of chronic diseaseswith no cure and one of the leading causes ofblindness worldwide. Open-angle glaucomaaccounts for 74% of all cases worldwide3.This eye condition is asymptomatic, and lessthan 50% of those with glaucoma are awareof their disease before blindness4. ElevatedIOP is the only known modifiable risk factorfor glaucoma and can typically be controlledwith daily administration of eye drops severaltimes a day, or in the most severe cases, withsurgery. In clinical studies, Simbrinza®

showed strong efficacy to lower the IOP levelfrom baseline by 23%-37%, while providingsustained IOP control throughout the day1.

“Based on the literature, up to 80%5 ofpatients deviate from their treatment regimen,resulting in poor adherence and the increasedrisk of progressive vision loss”, saidProfessor Barbara Cvenkel, MD, Head ofGlaucoma Unit, Eye Hospital Ljubljana,Slovenia and member of the ExecutiveCommittee of the European GlaucomaSociety (EGS). “When appropriate, the EGSrecommends the use of combinationtherapies, such as Simbrinza®, which providesa less complicated administration routine bydecreasing the number of eye drops to handleand reducing the treatment burden forpatients affected by this eye disease.”

The safety and efficacy of Simbrinza® isbased on two, pivotal six-month Phase III

studies evaluating the safety and efficacy ofSimbrinza® administered twice daily, andenrolled a total of 1,450 patients with open-angle glaucoma or ocular hypertension whowere insufficiently controlled onmonotherapy or were already using multipleIOP-lowering medications. The primaryendpoint for both studies was an assessmentof mean diurnal IOP change from baseline atthree months, with safety and supportiveefficacy evaluated through six months. Bothstudies met their primary endpoints1.

In clinical studies, the most frequentlyreported adverse drug reactions in patientstreated with Simbrinza® were ocular hyper -emia and ocular allergic type reactions1. Thesafety profile of brinzolamide 10 mg/mL andbrimonidine tartrate 2 mg/mL eye dropssuspension dosed twice daily (brinzolamide/brimonidine) was similar to that of theindividual components and did not result inadditional risk to patients relative to theknown risks of the individual components.

The results of these two studies will bepresented at the 32nd Congress of theEuropean Society of Cataract and RefractiveSurgeons (ESCRS) in London (UK) on 13-17September 2014 and during the ESCRSGlaucoma Day Programme on 12 Sept-ember 2014.

The launch of Simbrinza® in the EU willstart in the UK in the third quarter of 2014,followed by other European markets later in2014 and in 2015. In the U.S., Simbrinza®

was approved by the U.S. Food and DrugAdministration (FDA) and has been availablein the market since 2013.

References1. Alcon data on file, 2013.

2. Houde M; Prescription of topical antiglaucoma agentsfor patients with contraindications to beta-blockers;Can J Ophthalmol. 2003 Oct;38(6):469-75.

3. H A Quigley and A T Broman; The number of peoplewith glaucoma worldwide in 2010 and 2020; Br JOphthalmol. Mar 2006; 90(3): 262-267.

4. Quigley HA; Number of people with glaucomaworldwide; Br J Ophthalmol. 1996 May;80(5):389-93.

5. Olthoff CM1, Schouten JS, van de Borne BW, WebersCA; Noncompliance with ocular hypotensive treatmentin patients with glaucoma or ocular hypertension an evidence-based review; Ophthalmology. 2005Jun;112(6):953-61.

www.alcon.com

ROCHE

Roche to acquire SantarisPharma to expand discoveryand development of RNA-targeting medicinesRoche recently announced that it has agreed toacquire Santaris Pharma, a privately held bio -pharmaceutical company based near Copenhagen,Denmark. Santaris Pharma has pioneered itsproprietary Locked Nucleic Acid (LNA) platformthat has contributed to an emerging era of RNA-targeting therapeutics. This new class of medicineshas the potential to address difficult to treat diseasesin a range of therapeutic areas.

“Today there are many disease targets that arevery challenging or even impossible to reach withsmall molecules or antibodies,” said John C. Reed,Head of Roche Pharma Research and EarlyDevelopment. “We believe the LNA platformprovides the means to efficiently discover anddevelop an important new class of medicines thatmay address the significant needs of patients acrossmultiple therapeutic areas.”

“Roche and Santaris Pharma have comple -mentary capabilities that will help us realisebreakthrough medicines,” stated J. DonalddeBethizy, President and CEO of Santaris Pharma.“The acquisition combines Santaris Pharma’s next-generation antisense technology and LNA expertisewith Roche’s deep experience in disease biology,chemistry, drug safety, drug formulation, delivery,and development.”

The acquisition, which is subject to customaryclosing conditions, is expected to close in August2014. Roche plans to maintain Santaris Pharma’soperations in Denmark, where the existing site willbe renamed Roche Innovation Center Copenhagen.Under the terms of the agreement, Roche will make an upfront cash payment of USD 250 million to Santaris Pharma shareholders and make add-itional contingent payments of up to USD 200million based on the achievement of certainpredetermined milestones.

About the Locked Nucleic Acid (LNA) platformSantaris Pharma’s LNA platform and drug discoveryengine combines the company’s proprietary LNAchemistry with its highly specialised and targeteddrug discovery capabilities to rapidly deliver drugcandidates against both mRNA and microRNA, thusenabling scientists to develop drug candidates fordiseases that are difficult, or impossible, to targetwith contemporary drug platforms such as antibodiesand small molecules. The LNA platform is designedto overcome the limitations of earlier antisense andsiRNA technologies, in particular through a uniquecombination of small size, high binding affinity andmetabolic stability that allows this new class of drugscandidates to potently and specifically influenceRNA targets in many different tissues without theneed for complex delivery vehicles. LNA is alsosometimes referred to as BNA (Bicyclic or BridgedNucleic Acid).

www.roche.com

© A

ndre

y_Po

pov

/ Shu

tter

stoc

k.co

m

10 European Pharmaceutical Review VOLUME 19 ISSUE 4 2014 Catch up with daily news at www.europeanpharmaceuticalreview.com

NEWS: AROUND THE WORLD

GLAXOSMITHKLINE

Anoro® Ellipta® gainsapproval in Japan forthe treatment of COPDGlaxoSmithKline plc and Theravance, Inc.has announced that the Japanese Ministryof Health, Labour and Welfare (MHLW)has approved Anoro® Ellipta®(umeclidin -ium/vilanterol) for the relief of varioussymptoms due to airway obstruction withchronic obstructive pulmonary diseases(chronic bronchitis, pulmonary emphy -sema) (in the case where concurrent use oflong-acting inhaled muscarinic antagonistand long-acting inhaled beta2 agonist is required).

Anoro® is a once-daily combinationtreat ment comprised of two bronchodilators,umeclidinium (UMEC), a long-actingmuscarinic antagonist (LAMA), andvilanterol (VI), a long-acting beta2 agonist(LABA), in a single inhaler, the Ellipta®. Theapproved dose in Japan is UMEC/VI62.5/25mcg delivered once daily.

Darrell Baker, SVP & Head of GSKGlobal Respiratory Franchise, said, “Thereare many people living with COPD inJapan whose ability to breathe iscompromised by their condition. Our goalat GSK is to provide physicians with anexpanded range of COPD medicines whichenable a patient-centric approach totreatment, as recommended by globalguidelines. We are delighted that Anoro®

Ellipta® is now approved in Japan, makingit the first GSK COPD treatment to gainJapanese regulatory approval in five years,and we believe it will be an important newonce-daily dual bronchodilator treatmentoption for appropriate COPD patients.”

“We are very pleased with this latestregulatory approval for Anoro® Ellipta®,”said Rick E Winningham, Chief ExecutiveOfficer of Theravance. “This milestone is afurther demonstration of the ongoingsuccessful Theravance and GSK collabor -ation in respiratory medicine and we arelooking forward to being able to make thisnew medicine available for appropriateCOPD patients in Japan.”

Under the terms of the 2002 LABAcollaboration agreement, Theravance isobligated to make a milestone payment of$10 million (USD) to GSK followingMHLW approval of UMEC/VI in Japan.Following this approval, it is expected thatlaunch will take place in Japan in Q3 2014.

The MHLW assessment of UMEC/VIinvolved a review of eight phase III clinicaltrials, evaluating approximately 6,000COPD patients worldwide, including aspecific 52 week, open-label, long-termsafety study in Japanese patients.

www.gsk.com

NOVARTIS

Novartis provides drug candidate compounds to TB AllianceNovartis has signed an exclusive worldwidelicensing agreement with the Global Alliance forTB Drug Development (TB Alliance) forcompounds to fight tuberculosis (TB) that havebeen discovered at the Novartis Institutes forTropical Diseases (NITD).

According to the World Health Organisation,there are more than 8.6 million cases oftuberculosis each year, with more than 1.3million deaths reported annually. TB is a global disease, but has its deadliest impact inresource-poor countries1. Current therapies for TB require 6-30 month dosing regimes andthere are increasingly drug resistant strains of TB emerging2.

“TB is one of the scourges of the developingworld and new medicines are desperately neededto combat its continued spread,” said Mark C.Fishman, President of Novartis Institutes forBioMedical Research. “TB Alliance is wellplaced to take our discoveries and compoundsthrough development for the benefit of patientswith TB.”

“Our long-standing partnership withNovartis gives us confidence in the scientificunderpinnings of the TB portfolio,” says MelSpigelman, MD, President and CEO of TBAlliance. “We look forward to advancing themost promising compounds into the clinic tomeet the urgent need for new TB treatments.”

Under the terms of agreement, NITD willfully transfer its TB research and developmentprogram to TB Alliance, which will takefinancial and operational responsibility forcontinued research, development, approval anddistribution of compounds in the portfolio.Included is a novel class of drugs calledindolcarboxamides that are active against drugsensitive and multi-resistant strains of TB. One of these preclinical compounds NITD304,blocks MmpL3, a protein essential for the TB bacterium’s survival.

Novartis has collaborated in the past with TBAlliance and believes it has the best combinationof expertise, capacity, and strategic interest todevelop new agents and regimens for TB.

Novartis efforts in discovery of medicinesspecifically for the developing world continues,especially focused now on new therapies fortreating parasitic diseases such as malaria, andhuman African trypanosomiasis (HAT) – alsoknown as sleeping sickness, as well as viraldisease such as dengue fever.

References1. Global Tuberculosis Report 2013, World Health

Organization,http://www.who.int/tb/publications/global_report/gtbr13_executive_summary.pdf?ua=1

2. CDC, Treatment of Tuberculosis http://www.cdc.gov/mmwr/preview/mmwrhtml/rr5211a1.htm

www.novartis.com

ViiV Healthcare has recently announced that theU.S. Food and Drug Administration (FDA) hasapproved Triumeq® (abacavir 600mg,dolutegravir 50mg and lamivudine 300mg)tablets for the treatment of HIV-1 infection1.Triumeq® is ViiV Healthcare’s first dolutegravir-based fixed-dose combination, offering manypeople living with HIV the option of a single-pill regimen that combines the integrase strandtransfer inhibitor (INSTI) dolutegravir, with thenucleoside reverse transcriptase inhibitors(NRTIs) abacavir and lamivudine.

Triumeq® alone is not recommended for usein patients with current or past history ofresistance to any components of Triumeq®.Triumeq® alone is not recommended in patientswith resistance-associated integrase substitutionsor clinically suspected INSTI resistance becausethe dose of dolutegravir in Triumeq® isinsufficient in these populations. Beforeinitiating treatment with abacavir-containingproducts, screening for the presence of a geneticmarker, the HLA-B*5701 allele, should beperformed in any HIV-infected patient,irrespective of racial origin. Products containingabacavir should not be used in patients known tocarry the HLA-B*5701 allele1.

Dr Dominique Limet, Chief ExecutiveOfficer at ViiV Healthcare, said: “The approvalof Triumeq® offers many people living with HIVin the U.S. the first single-pill regimencontaining dolutegravir. ViiV Healthcare iscommitted to delivering advances in care andnew treatment options to physicians and peopleliving with HIV. We are proud to announce thisimportant milestone, marking the second newtreatment to be approved in the U.S. from ourpipeline of medicines.”

This FDA approval is based primarily upon datafrom two clinical trials:■ The Phase III study (SINGLE) of treatment-

naïve adults, conducted with dolutegravir andabacavir/lamivudine as separate pills2,3

■ A bioequivalence study of the fixed-dosecombination of abacavir, dolutegravir andlamivudine when taken as a single pillcompared to the administration ofdolutegravir and abacavir/lamivudine asseparate pills4

In the SINGLE study, a non-inferiority trial with a pre-specified superiority analysis, more patients were undetectable (HIV-1 RNA

VIIV HEALTHCARE

ViiV Healthcare receives FDA approval for Triumeq®, a new single-pill regimen for thetreatment of HIV-1 infection

Catch up with daily news at www.europeanpharmaceuticalreview.com VOLUME 19 ISSUE 4 2014 European Pharmaceutical Review 11

NEWS: AROUND THE WORLD

BIOGEN IDECS

Biogen Idec’s PLEGRIDY™approved in the U.S. fortreatment of multiple sclerosisBiogen Idec has revealed that the U.S. Food and DrugAdministration (FDA) has approved PLEGRIDYTM

(peginterferon beta-1a) – a new treatment for people withrelapsing forms of multiple sclerosis (RMS).PLEGRIDYTM, the only pegylated beta interferonapproved for use in RMS, is dosed once every two weeksand can be administered subcutaneously with thePLEGRIDY PEN, a new, ready-to-use autoinjector, or aprefilled syringe.

“PLEGRIDYTM offers people with MS robustefficacy, a safety profile consistent with the establishedinterferon class, and significantly fewer injections thanother beta interferon treatments,” said George A. Scangos,Ph.D., Chief Executive Officer of Biogen Idec.“PLEGRIDYTM represents the most significant innovationin the interferon class in over a decade, and is the result ofour deep commitment to improving the lives of peoplewith MS and those who care for them.”

The FDA approval of PLEGRIDYTM is based onresults from one of the largest pivotal studies of betainterferon conducted, ADVANCE, which involved morethan 1,500 MS patients. ADVANCE was a two-year,Phase 3, placebo-controlled (in year one) study thatevaluated the efficacy and safety of PLEGRIDYTM

administered subcutaneously. The analysis for all primaryand secondary efficacy endpoints occurred at the end ofyear one. After the first year, patients on placebo receivedPLEGRIDYTM for the duration of the study.

In the first year of the ADVANCE clinical trial,PLEGRIDYTM dosed once every two weekssignificantly reduced annualised relapse rate (ARR) at oneyear by 36% compared to placebo (p=0.0007).PLEGRIDYTM reduced the risk of 12-week con-firmed disability progression, as measured by theExpanded Disability Status Scale, by 38% (p=0.0383)compared to placebo. PLEGRIDYTM also significantlyreduced the number of new gadolinium-enhancing [Gd+] lesions by 86% (p<0.0001) and reduced new or newlyenlarging T2-hyperintense lesions by 67% (p<0.0001)compared to placebo.

The most common adverse reactions were injectionsite reaction, flu-like illness, fever, headache, muscle pain,chills, injection site pain, weakness, injection site itchingand joint pain. The ADVANCE two-year safety data wereconsistent with safety results observed in year one.

“PLEGRIDYTM is a compelling new treatment optionfor people living with MS that offers a proven safetyprofile, strong efficacy and an every two week dosingschedule administered by an innovative delivery system,”said Peter Wade, M.D., Medical Director for Neurology atthe Mandell Center for Comprehensive Multiple SclerosisCare and Neuroscience Research in Hartford, CT. “As atreating neurologist, I believe these attributes will appealto MS patients who look for less frequent dosing withproven effectiveness.”

PLEGRIDYTM has been recently approved by theEuropean Commission.

“It is always encouraging to have additional treatmentoptions that may help people with MS manage theirdisease as we move towards our ultimate goal of endingMS forever,” said Dr. Timothy Coetzee, Chief Advocacy,Services and Research Officer at the National MS Society.

www.biogenidec.com

SANOFI

Sanofi and MannKind announce global licensingagreement for Afrezza® rapid-acting inhaled insulinSanofi and MannKind Corporation have entered into a worldwide exclusive licensingagreement for development and commercialisation of Afrezza® (insulin human)Inhalation Powder, a new rapid-acting inhaled insulin therapy for adults with type 1 andtype 2 diabetes. The companies plan to launch Afrezza® in the United States in the first quarter of 2015.

Under the collaboration and license agreement, Sanofi will be responsible for globalcommercial, regulatory and development activities. Under a separate supply agreement,MannKind will manufacture Afrezza® at its manufacturing facility in Danbury,Connecticut. In addition, the companies are planning to collaborate to expandmanufacturing capacity to meet global demand as necessary.

Under the terms of the agreement, MannKind Corporation will receive an upfrontpayment of $150 million and potential milestone payments of up to $775 million. The milestone payments are dependent upon specific regulatory and development targets, as well as sales thresholds. Sanofi and MannKind will share profits and losses ona global basis, with Sanofi retaining 65% and MannKind receiving 35%. Sanofi hasagreed to advance to MannKind its share of the collaboration’s expenses up to a limit of$175 million.

“Afrezza® is an innovative drug-device combination product consisting of a dry formulation of human insulin delivered through a small, discreet inhaler,” said Pierre Chancel, Sanofi Senior Vice President Diabetes Division. “Afrezza®

is a further addition to our growing portfolio of integrated diabetes solutions. It is uniquely positioned to provide patients with another insulin therapy option to manage their diabetes but does not require multiple daily injections.”

“We are so very pleased andhonoured that Sanofi has joinedwith MannKind to bring Afrezza® topatients with diabetes worldwide,”stated Alfred Mann, MannKind’sChairman and Chief ExecutiveOfficer. “Sanofi is the ideal partner given their complementaryproduct portfolio, their vast insulinmarket presence and a leadingglobal commercial infrastructure.Our profit-sharing agreement aligns the interests of MannKindand Sanofi to optimise develop -ment, commercialisation andmanufacturing costs.”

Sanofi’s diabetes solutionsportfolio includes medications aswell as drug delivery systems andblood glucose monitoring devices.As a leader in diabetes management,the addition of Afrezza® to Sanofi’sleading portfolio of pharmaceuticalsrepresents the latest opportunity forthe company to bring anotherinsulin option to people withdiabetes around the globe.

The closing of the transaction issubject to customary Hart-Scott-Rodino approval and completion offinancing documentation. .

Greenhill & Co. served asexclusive financial advisor toMannKind with respect to thistransaction.

www.sanofi.com

© M

iner

va S

tudi

o / S

hutt

erst

ock.

com

<50 copies/mL) in the dolutegravir andabacavir/lamivudine arm (the separatecomponents of Triumeq®) than in theAtripla®†(efavirenz, emtricitabine andtenofovir) arm, the most commonly usedsingle-pill regimen. The difference wasstatistically significant and met the pre-specified test for superiority. The differencewas driven by a higher rate of discontinuationdue to adverse events in the Atripla arm2,3.

At 96 weeks, 80% of participants on thedolutegravir-based regimen were virologicallysuppressed compared to 72% of participants onAtripla. Grade 2-4 treatment emergent adversereactions occurring in 2% or more partici-pants taking the dolutegavir-based regimenwere insomnia (3%), headache (2%) andfatigue (2%)3.

References1. Triumeq US label2. Walmsley SL, Antela A, Clumeck N et al; for the

SINGLE Investigators. Dolutegravir plusabacavir–lamivudine for the treatment of HIV-1infection. N Engl J Med. 2013;369(19):1807-1818.

3. Walmsley S, Berenguer J, Khuong-Josses M, et al.Dolutegravir regimen statistically superior toefavirenz/tenofovir/emtricitabine: 96-week results fromthe SINGLE study (ING114467). Poster presented at:21st Conference on Retroviruses and OpportunisticInfections; March 3-6, 2014; Boston, MA. Poster 543.

4. Weller S, Chen S, Borland J et al. Bioequivalence of aDolutegravir, Abacavir and Lamivudine Fixed-DoseCombination Tablet and the Effect of Food. JAIDS. 2014May doi: 10.1097/QAI.0000000000000193.http://journals.lww.com/jaids/Abstract/publishahead/Bioequivalence

www.viivhealthcare.com

Pharmaceutical protein productionWhile proteins of interest are still isolated from natural extracts9, theadvent of modern molecular biology techniques has made recombinantprotein expression the mainstream methodology for pharmaceuticalproduction9-11. The main drivers for the use of recombinant proteins are:(i) low availability of native protein (e.g. the annual use of amylase andxylose isomerase is over 95,000 tons each12); (ii) livestock infections for

the production of vaccines and subsequent economic loss13; (iii) immune responses to animal proteins after injection (e.g. insulin)12;and (iv) reproducibility of protein production in relation to its quality.

Since the implementation of recombinant DNA in the early-1970s,proteins have been expressed in many different organisms and(derived) cell types, such as bacteria, yeasts, moulds, insects, protozoa,mammals, plants, transgenic plants and animals and with the use of

Pharmaceutical biotechnology is big business; it currently consists of 1/6 of the total volume of the pharmaceuticalmarket and continues to grow steadily1-5. Expression of therapeutic proteins is mainly done in living cells, although‘cell free protein synthesis’ (CFPS) or ‘in-vitro transcription translation’ (IVTT) is beginning to emerge as analternative for commercial production6,7. In this article we will highlight some of the more recent advances in proteinexpression systems8 for the production of pharmaceutical proteins. We will also discuss current trends in theengineering of pharmaceutical proteins with improved properties.

PROTEIN EXPRESSION

Engineering cells andproteins – creatingpharmaceuticals

Marco Casteleijn andDominique RichardsonUniversity of Helsinki


© fu

sebu

lb /

Shut

ters

tock

.com

cell lysate in CFPS. During recombinant protein expression a gene isintroduced in an organism (or its derivative) followed by constitutive- orinduced-translation and transcription. Choosing the correct expressionsystem is protein dependent and factors such as protein quality,functionality, production speed and yield are most important7,11,12.

As of 2014, overall trends in recombinant protein production showan increase in the use of Chinese hamster ovary(CHO) and yeast cells, while there has been adecrease in the use of other mammalian andEscherichia coli (E. coli) systems (see Figure 1,page 14). Production of non-glycosylatedproteins is conducted mainly in bacteria oryeast (45%, May 2014), while the production ofglycosylated proteins is carried out predomi -nantly in CHO cells (29% compared to mammalian cells, insect cells and transgenic-animals and -plants at 26% (see Figure 1, page 14). More than a decade ago about 20 pharmaceutical proteins wereproduced by transgenic technology for clinical trials14, however the highdevelopmental costs for these production systems clearly hindered theadvancement of this method2,14. Other emerging systems in the marketinclude the use of P. pastoris and H. polymorpha – both of which arediscussed hereafter.

Escherichia coli (E.coli)During the 1980s, E. coli was the dominating organism of choice forrecombinant protein production15, and E. coli derived pharmaceuticalproteins still account for 29% of marketed biologics. Due to the longhistory of its use and deep understanding of the E. coli genetics, much

progress has been made in the engineering of E. coli strains for theproduction of proteins an plasmids10,12,16-19.

E. coli is a good choice for the first effort to produce a recombinantprotein15, and a consensus protocol has been developed recently as a guide to start E. coli protein expression20. It can be cultivated witha relatively cheap defined media (e.g. glucose, ammonia phosphate

and some minerals) and strategies for low cost production have been developed15,21. E. coli has clear advantages; however draw -backs include the incorrect formation ofmultiple disulfide bonds, non-extracellularproduction, and limited PTMs (e.g. glycosyla -tion is not possible). Moreover, E. coli producespyrogenic endotoxins, although various

methods can be employed for their removal22. Typical protein yields arein the range of 20-400 mg/L medium (see Figure 2, page 14).

YeastSaccharomyces cerevesiae (S. cerevesiae), Pichia pastoris (P. pastoris)and Hansenula polymorpha (H. polymorpha) are currently the onlythree expression strains used in the production of marketedpharmaceutical proteins (see Figure 1, page 14). Yeasts are single-celledeukaryotic fungal organisms, and the major advantages of its use are:high yield (see Figure 2, page 14); stable production strains; durability;cost effective; high density growth; high productivity; suitability forproduction of isotopically-labelled protein; rapid growth in chemicallydefined media; product processing similar to mammalian cells; canhandle S–S rich proteins; can assist protein folding; and its ability to

PROTEIN EXPRESSION

While proteins of interest are stillisolated from natural extracts,

the advent of modern molecular biology techniques has made

recombinant protein expression themainstream methodology forpharmaceutical production

glycosylate proteins12. Proteins that do not fold correctly in E. coli or thatrequire glycosylation for its function are often produced in yeast.

Like E. coli, S. cerevesiae has a comparatively well-characterisedgenome and since the organism has no pathogenic properties it is classified as GRAS (generally regarded as safe). In general, S. cerevesiae is good alternative to E. coli, however the complexglycosylation patterns are often unacceptable for mammalian proteins because the O-linked oligosaccharides contain only mannosewhereas higher eukaryotic proteins have sialylated O-linked chains.Additionally, N-linked sites are over-glycosylated, high mannose typestructures which can lead to immunological responses and rapidclearance rates12,23.

The methylotrophic yeast P. pastoris is an effective and versatilesystem for the expression of heterologous proteins24. Its growingpopularity can be attributed to several factors: (i) easy accessibility towell-established molecular biology techniques developed for S. cerevesiae; (ii) its ability to express proteins at high levels (eitherintracellular or extracellular); (iii) performs PTMs (i.e. glycosylation,disulfide bond formation, and proteolytic processing); (iv) the expression system is available as a commercial kit; (v) tightlyregulated promoter systems were developed (e.g. AOX1, up to 1000 foldup-regulation); and (vi) capable of enduring high cell densitycultivations in a bioreactor and the preference of a respiratory- over afermentative-growth model25,26. Glycosylation is less extensive in P. pastoris than in S. cerevisiae27. N-linked high-mannoseoligosaccharides are usually up to 20 residues. Human-like hybrid

and complex N-glycans were generated in P. pastoris28,29, and thesesystems are currently optimised30-32.

An in-depth review of H. polymorpha by Gotthard and co-workershighlights its strengths for pharmaceutical protein production33. In short, the generation of recombinant H. polymorpha strains typicallyemploys vectors, traditionally circular plasmids, which are mitoticallystable being integrated into the genome of the host. Integration over anumber of generations may result in strains with as many as 100 integrated plasmids present in tandem repeats. A major advantageof H. polymorpha is that proteins can be secreted into the media, orinto a pre-selected cell compartment, such as the peroxisome, thevacuole, or targeted to the cell surface. For secreted phytase, productlevels of up to 13.5 g/L have been obtained.

Compared to S. cerevisiae, the high mannose glycan chains of


PROTEIN EXPRESSION

Figure 2: Maximum yields in mg/L of the main expression systems for twopharmaceutical proteins7,12. *) Cell Free Protein Synthesis, **) Insect cell expression0.4 mg/L and no CFPS data.

Figure 1: Distribution of expressions systems used for the production of 245 approved pharmaceutical proteins (all) Volume of the other bars is: >2000, 106 proteins; 2001-2006, 44 proteins; 2006-2010, 54 proteins; 2011-2014 (first 4 months), 41 proteins *) Including S. cerevesiae, P. pastoris, H. polymorpha; **)including baby hamster kidney cells (BKH), murine cells, Sp2/0 cells, V cholera(one vaccine), hybridoma cells, or not specified mammalian cells1-5,14,48.

Fungal expression systemsFilamentous fungi are the main sources for the production of manycommercial enzymes and organic compounds. However, while fungalstrains such as Aspergillus niger are also being used to produce therapeuticproteins like monoclonal antibodies, use of fungal expression systems forpharmaceutical applications is not common. Recently, it was revealed(Visser et al., 2011) that the C1 Expression System, developed by DyadicInternational, Inc. and based on a Myceliophthora thermophila fungus,offers important benefits to commercial development and production ofproteins for amongst others pharmaceutical applications.

The C1 Expression System has many similar advantages as yeast for theexpression and production of pharmaceutical proteins: a diverse post-translational modifications system, protein folding and secretionmechanisms, the ability to produce S–S rich proteins and a glycosylationsystem. The C1 Expression System also demonstrates important advantagesover yeasts and other fungal strains. Dyadic has demonstrated that C1 canproduce and secrete different heterologous proteins based on genesoriginating from bacteria, fungi, mammalian cells and viruses. The latter iscurrently being explored in collaboration between Dyadic and SanofiPasteur as a new source for the production of vaccines. C1 also has thecapacity to produce and secrete high levels of single heterologous proteins.Since up to 80% of the secreted protein (up to 80 grams per litre) iscomprised of the target protein, the purification system is relatively easy andat low cost. Finally, the fact that C1 glycosylation motives resemble thehumane glycosylation pattern can potentially lead to faster and moresuccessful drug development with lower risk of immune responses inpatients or no downstream effectors functions.

In addition to the characteristics that make it an attractive potentialproduction host, the C1 Expression System’s proven track record in theindustrial world highlights its capabilities. C1 has been fermented onindustrial (up to 500 m3) scale under diverse production conditions withbroad pH (5-9) and temperature (25-43°C) ranges tailored for the protein tobe expressed.

www.dyadic.nl

N-linked oligosaccharides generally appear to be much shorter in H.polymorpha; typical oligosaccharide species attached to therecombinant protein have Man8-12 GlcNAc2-structures without terminalα-1,3-linked mannose residues. Therefore, the outer chain processing inthe N-linked glycosylation pathway in H. polymorpha appears to besimilar to that in P. pastoris, with the addition of shorter mannosestructures and lack of any terminal α-1,3-linked mannose residues.

Mammalian cellsToday over 50% of all recombinant protein pharmaceuticals areproduced in mammalian cells (see Figure 1, page 14). Driven by the needof PTMs of pharmaceutical proteins, these relatively complexexpression systems have increased their yields tremendously due todevelopments in bioprocess engineering, media optimisation, andstrain engineering since the 1980s34 . While adherent cell cultures areused in industrial setting, suspended cell cultures (e.g. CHO cell- andBKH cell-cultures), and for even more increased yields, extended batchcultures and perfusion processes in phase III- or the production-phaseare most abundant.

While biopharmaceuticals requiring relatively little or no PTM’s canbe made in platforms ranging from E. coli to mammalian cells,glycoproteins and other pharmaceuticals requiring more complexPTM’s, e.g. glycosylation, mammalian cell lines are the only viableoption. This is because the final glycosylation pattern of recombinantproteins is determined by the expression platform; it is well known thatthere are significant differences in glycan structures between proteinsexpressed in human, mammalian and yeast cells (see Figure 3). As such,the majority of therapeutic glycoproteins are expressed in mammaliancell lines (e.g. CHO cells)35.

However, the drawbacks to mammalian expression include thenumber of glycoforms that are expressed and the differences in protein glycosylation between different mammalian cell lines36. For example, glycoproteins expressed in some cell lines, including CHO cells, contain terminal Neu5Gc (N-glycolylneuraminic acid) rather than the human Neu5Ac (N-acetylneuraminic acid). These non-human sialic acids moieties may affect immunogenicity as antibodies against the Neu5Gc have been identified35. Expression insome cell lines, e.g. epoetin delta in human fibrosarcoma cell line

PROTEIN EXPRESSION


Figure 3: Glycan chains produced when utilising different glycoprotein expression systems. Yeast expression systems yield high mannose type glycan chains. Human andanimal expression systems yield very similar glycan structures; however animal expression systems yield both Neu5Ac and Neu5Gc moieties, while humans have lost theability to synthesize Neu5Gc.

Table 1: Overview of PEGylated biopharmaceuticals on the current market

Manufacturer Expression Number and position

Function (approval year) system of PEG moieties

Granulocyte-Colony stimulating Factor Teva (2013 EU) E. coli A 20-kDa PEG-sialic acid derivative attached at the natural O-glycosylation site of G-CSF

Cyclic peptide dimer acting as a erythropoiesis Affymax (2012)* Synthetic peptide A 20 amino acid synthetic cyclic peptide dimer conjugatedstimulating agent via a 40kDa branched PEG linker

Recombinant urate oxidase Savient (2010-FDA, 2013- EU) E. coli 9 ± 1 strands of a 10-kDa PEG moiety conjugated via Lysine residues

Anti-TNF-alpha humanized antibody UCB Pharma (2008) E. coli A 40kDa PEG moiety is attached via a 'free' cysteine onfab' fragment the mAb fragment

Erythropoiesis stimulating agent Roche (2007) CHO Epoetin beta conjugated to a 30kDa PEG at positions Lys52 or Lys46

Anti-vascular endothelial growth factor Pfizer (2004) Synthetic aptamer A 40kda PEG moiety is attached at the 5' of(VEGF) RNA aptamer the RNA sequence

Human growth hormone antagonist Pfizer (2003) E. coli 4-6 5kDa-PEG moieties are conjugated to Lysines and the N-terminus of the growth hormone

Granulocyte-Colony stimulating Factor Amgen (2002) E. coli A 20kDa PEG attached via the N-terminal amino group

Interferon alpha for treatment of Hepatitis C Hoffman-La-Roche (2002) E. coli Conjugated to a branched 40kDa PEG via lysine residue

Interferon alpha for treatment of Hepatitis C Schering-Plough and Enzon (2000) E. coli Conjugated to a12kDa PEG via lysine residues

Asparaginase Enzon (1994) E. coli 5kDa PEG conjugated to Lysine residues

Adenosine deaminase Enzon (1990) E. coli 5kDa PEG conjugated to Lysine residues

*) Withdrawn in 2013 due to safety reasons (FDA)

HT-1080, can result in glycan chains with no terminal Neu5Gc residues37, however this method is not always a possibility. One way tocircumvent this problem, as well as other issues with PTM such asdisulfide bond formation is to engineer cell lines to express proteinswith the correct PTMs38.

Future outlookWhile transient gene expression in mammalian cells is a maturingtechnology it is not yet approved for pharmaceutical proteinproduction39. Engineering mammalian gene switches and post-transcriptional control (e.g. via RNA aptamer-intramer fusions) will givelight to new expression strains: (i) as part of autologous cell therapies,gene circuits encode computational operations that can beprogrammed by intracellular signals to execute specific tasks, (ii) cellimplants consisting of engineered allogeneic or xenogeneic mammaliancells could be plugged into the metabolism of patients to sense andrespond to specific biomarkers40.

In addition, the trypanosomatid protozoa Leishmania tarentolae (anonpathogenic parasite) is under investigations as an alternativeproduction-system for pharmaceutical proteins due to its complexPTMs and significantly easier cultivation requirements thanmammalians cells41-45.

Finally, with the first successful commercial production of

antibodies in CFPS for the pharmaceutical industry by Sutro Biopharma,CA, USA in a 100 L tank6,7,46 the road is open to start producing morepharmaceutical proteins in not only E. coli lysates, but also eukaryotecell lysates.

Engineering of biopharmaceuticals Protein engineering can span a wide field of modifications andconjugations including gene manipulations, glycosylation, PEGylation,albumin fusion, PASylation, fatty acid conjugation, amidation, disulfidebond shuffling, and Fc fusion. Here focus on protein engineeringmethods applied post-expression for improved stability, solubility,potency, reduced immunogenicity, increased proteolytic resistance,and/or improved serum half-life.

GlycoengineeringN-linked glycosylation is known to mediate a wide spectrum offunctions; the most important of which (in terms of proteinpharmacokinetics) include activity, stability, solubility, folding,immunogenicity and in-vivo half-life. As such, pharmaceuticalglycoproteins that are expressed non-glycosylated (i.e. in E. coli) canexhibit impaired in-vivo activities and in some cases complete loss ofin-vivo activity is observed. Recombinant human interferon-β (rhIFN-β)is an example of a naturally glycosylated protein that is active


PROTEIN EXPRESSION

1. Walsh G.Biopharmaceutical benchmarks. Nature Biotechnology, 2003, 21, 865-870

2. Walsh G. Biopharmaceutical benchmarks. Nature Biotechnology, 2010, 28, 917-924

3. Walsh G. A review of new biologic drug approvals over the years, featuring highlights from2010 and 2011. Biopharm International, 2012, 6, 34-36

4. Walsh G. Milestones and moderate progress in 2012 drug approvals. BiopharmInternational, 2013, 26, 54-56

5. Walsh G. Biopharmaceutical approval trends in 2013. Biopharm International, 2014 (onlineMay 27th, 2014: http://www.biopharminternational.com/biopharm/Business/Biopharmaceuticals-Approval-Trends-in-2013/ArticleStandard/Article/detail/839471)

6. Swartz JR. Transforming biochemical engineering with cell-free biology. AIChE Journal,2012, 58, 5–13

7. Casteleijn MG, Urtti A, Sarkhel S Expression without boundaries: Cell-free protein synthesisin pharmaceutical research International Journal of Pharmaceutics, 2013, 440, 39-47

8. Lutz S, Bornscheuer UT Protein Engineering Handbook 2008, (1st ed)Wiley-VCH, Weinheim

9. Rader RA. FDA Biopharmaceutical Product Approvals and Trends in 2012; Up from 2011,but Innovation and Impact Are Limited. BioProcess International, 2013, 11, 18-27

10. Hunt I. From gene to protein: a review of new and enabling technologies for multi-parallelprotein expression. Protein Expression and Purification, 2005, 40, 1-22

11. Schmidt FR. From Gene to Product: The Advantage of Integrative Biotechnology. Gad SC(Editor) Handbook of Pharmaceutical Biotechnology, 2007, 2-38

12. Demain AL, Vaishnav P Production of recombinant proteins by microbes and higherorganisms Biotechnology Advances, 27, 2009, 297-306

13. Jayaraj R, Smooker PM. So you Need a Protein – A Guide to the Production of RecombinantProteins. The Open Veterinary Science Journal, 2009, 3, 28-34

14. Walsh G. Biopharmaceutical benchmarks. Nature Biotechnology, 2000, 18, 831-8333.

15. Enfors SO, Häggström L. Bioprocess Technology Fundamentals and Applications (1st edition). Högskoletryckeriet, Royal Insitute of Technology (KTH), Stockholm (2000)

16. Chou CP. Engineering cell physiology to enhance recombinant protein production inEscherichia coli. Applied Microbioly and Biotechnology, 2007, 76, 521–532

17. Samuelson JC. Recent Developments in Difficult Protein Expression: A Guide to E coliStrains, Promoters, and Relevant Host Mutations. Thomas CE Jr, Ming-Qun X (Editors).Heterologous Gene Expression in E coli: Heterologous Gene Expression in Ecoli, Methodsin Molecular Biology, 2011, 705, 195-209

18. Baneyx F. Recombinant protein expression in Escherichia coli. Current Opinion inBiotechnology, 1999, 10, 5, 411–421

19. Casali N. Escherichia coli Host Strains. Preston A (Editor) E coli Plasmid Vectors: Methodsin Molecular Biology™, 2003, 235, 27-48

20. Gräslund S, Nordlund P, Weigelt J, Hallberg BM, Bray J, Gileadi O, Knapp S, OppermannU, Arrowsmith C, Hui R, Ming J, dhe-Paganon S, Park H-W, Savchenko A, Yee A, EdwardsA, Vincentelli R, Cambillau C, Kim R, Kim S-H, Rao Z, Shi Y, Terwilliger TC, Kim C-Y,

Hung L-W, Waldo GS, Peleg Y, Albeck S, Unger T, Dym O, Prilusky J, Sussman JL, StevensRC, Lesley SA, Wilson IA, Joachimiak A, Collart F, Dementieva I, Donnelly MI,Eschenfeldt WH, Kim Y, Stols L, Wu R, Zhou M, Burley SK, Emtage JS, Sauder JM,Thompson D, Bain K, Luz J, Gheyi T, Zhang F, Atwell S, Almo SC, Bonanno JB, Fiser A,Swaminathan S, Studier FW, Chance MR, Sali A, Acton TB, Xiao R, Zhao L, Ma LC, HuntJF, Tong L, Cunningham K, Inouye M, Anderson S, Janjua H, Shastry R, Ho CK, Wang D,Wang H, Jiang M, Montelione GT, Stuart DI, Owens RJ, Daenke S, Schütz A, HeinemannU, Yokoyama S, Büssow K, Gunsalus KC. Protein production and purification. NatureMethods, 2008, 5, 135-146

21. Peti W, Page R. Strategies to maximize heterologous protein expression in Escherichia coliwith minimal cost. Protein Expression and Purification, 2007, 51 1–10

22. Petsch D, Anspach FB. Endotoxin removal from protein solutions. Journal ofBiotechnology, 2000, 76, 97-119

23. Nasaba FP, Aebia M, Bernhardb G, Frey AD. A Combined System for EngineeringGlycosylation Efficiency and Glycan Structure in Saccharomyces cerevisiae. Applied andEnvironmental Microbiology, 2013, 79, 997-1007

24. Potvin G. Ahmad A. Zhang Z. Bioprocess engineering aspects of heterologous proteinproduction in Pichia pastoris: A review. Biochemical Engineering Journal, 2012, 64, 91-105

25. Cereghino GP, Cereghino JL, Ilgen C, Cregg JM. Production of recombinant proteins infermenter cultures of the yeast Pichia pastoris. Current Opinion in Biotechnology, 2002, 13, 329-332

26. Cereghino JL, Cregg JM. Heterologous protein expression in the methylotrophic yeastPichia pastoris. FEMS Microbiology Reviews, 200, 24, 45–66

27. Dale C, Allen A, Fogarty S. Pichia pastoris: a eukaryotic system for the large-scaleproduction of biopharmaceuticals. Biopharm, 1999, 12, 36–42

28. Choi BK, Bobrowicz P, Davidson RC, Hamilton SR, Kung DH, Li H, Miele RG, Nett JH,Wildt S, Gerngross TU. 2003. Use of combinatorial genetic libraries to humanize N-linkedglycosylation in the yeast Pichia pastoris. PNAS, 2003,100, 5022–5027

29. Hamilton SR, Bobrowicz P, Bobrowicz B, Davidson RC, Li H, Mitchell T, Nett JH, RauschS, Stadheim TA, Wischnewski H, Wildt S, Gerngross TU. Production of complex humanglycoproteins in yeast. Science, 2003, 301, 1244–1246

30. Vervecken W, Kaigorodov V, Callewaert N, Geysens S, De Vusser K, Contreras R. In vivosynthesis of mammalian-like, hybrid-type N-glycans in Pichia pastoris. Applied andEnvironmental Microbiology, 2004, 70, 2639–2646

31. Bobrowicz P, Davidson RC, Li H, Potgieter TI, Nett JH, Hamilton SR, Stadheim TA, MieleRG, Bobrowicz B, Mitchell T, Rausch S, Renfer E, Wildt S. Engineering of an artificialglycosylation pathway blocked in core oligosaccharide assembly in the yeast Pichia pastoris:production of complex humanized glycoproteins with terminal galactose. Glycobiology,2004 14,757–766

32. Hamilton SR, Davidson RC, Sethuraman N, Nett JH, Jiang Y, Rios S, Bobrowicz P,Stadheim TA, Li H, Choi BK, Hopkins D, Wischnewski H, Roser J, Mitchell T, StrawbridgeRR, Hoopes J, Wildt S, Gerngross TU. 2006. Humanization of yeast to produce complexterminally sialylated glycoproteins. Science 313:1441–1443

References

References continued on page 18

Materials Development • Testing • Assurance

SUPPORTING PHARMACEUTICAL MANUFACTURERS

We’ve just opened brand new, state-of-the-art laboratories to

provide you with all the pharmaceutical quality control testing

you need.

Our services include: Pharmacopoeial QC testing, method

development and validation, stability storage and testing, and

water analysis.

With fast turnaround times, quality data and experienced

scientists, why not give us a try?

We don’t just provide numbers though – using our vast range

of analytical services and our expertise in surface analysis

and materials technologies, we can help you to optimise your

materials, products, processes and profits.

NEW

PHARM

ACEUTIC

AL

QUALITY

CO

NTR

OL TE

STING

LABO

RATO

RIE

S

www.lucideon.com/epr

in-vivo when expressed from E. coli (i.e. non-glycosylated)47. However, while both the glycosylated and non-glycosylated variant isavailable as a biopharmaceutical, the solubility and activity of the non-glycosylated variant is impaired in relation to its glycosylatedcounterpart. This example highlights the importance of glycosylation inthe context of pharmaceutical proteins and the ability to controlglycosylation is continually progressing.

Approaches to glycoengineering can vary widely. The most highlycited example of successful glycoengineering is darbepoietin alfa, thelong acting erythropoietin derivative that mediates red blood cellproduction for the treatment of anemia in association with chronickidney disease (CKD) and/or chemotherapytreatment48,49. Epogen/ Procrit was the firsterythropoiesis-stimulating agent (ESA) to beapproved in 1989 and the active ingredient,epoetin alfa, is recombinant humanerythropoietin expressed in CHO cells.Darbepoietin alfa, marketed as Aranesp byAmgen in 2001, has two additional N-linked glycosylation sitesengineered into the peptide backbone. The resulting increase in sialicacid content gives Aranesp a lower affinity for the EPO receptor(Aranesp IC50 of 1.05 compared to epoetin alfa IC50 of 0.54 ng) but anincreased serum half-life (Aranesp has a t1/2 of 26 hours compared to8.5 hours for epoetin alfa)50. As a result, Aranesp can be administeredless frequently than epoetin alfa products.

While Aranesp is the only approved drug utilising this methodology,recent examples of ‘hyperglycosylated’ proteins with an improved half-life include coagulation factor IX (four additional glycosylation siteswere introduced to yield a variant with a 2.4 fold increase in half-life)51,recombinant human IFN-alpha2 (4- and 5-N-linked IFN variants showed

a 25-fold increase in half-life compared to the non-glycosylated hIFN-alpha2)52, human alpha 1-antitrypsin, A1AT (one additionalglycosylation site at various positions yielded variants with up to a 3.6-fold longer serum half-life)53, and follicle-stimulating hormone, FSH, (introduction of 4 additional N-linked glycosylation sites yielded avariant with a 2-fold increase in half-life)54. Interestingly, in the case ofthe FSH, both N- and O-linked glycosylation sites were introduced into the protein. While the N-linked variants showed a significantlyincreased half-life compared to the O-linked variants, it highlights theuse of a relatively less understood and underexploited form of PTM54.Other approaches to glycoengineering include the generation of

afucosylated glycoproteins and antibodies,enzymatic cleavage/ addition of glycans and glycoPEGylation55-60.

PEGylation PEGylation is by far the most prominentconjugation strategy currently used to improve

the pharmacokinetics of therapeutic proteins. PEGylation was originallyintroduced as a method to prevent immune responses in patients;however since then it has emerged as a versatile tool to increasesolubility, reduce toxicity and prevent protein aggregation.

The currently available PEGylated biopharmaceuticals span a range of therapeutics with modifications ranging from the addition of a single PEG moiety up to the addition of 9 PEG moieties (see Table 1, page 15)61-74. Despite the success of PEGylated proteins in themarket, a shortcoming to PEGylation technology is the limited controlover the site of ligation; PEG is most often ligated to proteins viaaccessible amino groups, either the N-terminus or surface lysineresidues. Approaches to achieve site specific conjugation revolve

PROTEIN EXPRESSION

E. coli is a good choice for the first effort to produce a recombinant protein,

and a consensus protocol has beendeveloped recently as a guide to start

E. coli protein expression

around the exploitation of naturally occurring ‘handles’ for ligation suchas the modification/introduction of a ‘free’ cysteine75-78 and the use ofnaturally occurring glycosylation sites, e.g. glycoPEGylation.

In some cases PEGylation can result in lower in-vitro activities asthe modification can be within a receptor binding region or active site;however, this loss of in-vitro activity is usually compensated for by an increase in in-vivo activity as a result of increased circulating half-life79-83. This is the case for Mircera, a PEGylated epoetin beta thatacts as a continuous erythropoietin receptor activator80. Afterexpression in CHO cells, epoetin beta is chemically modified with asingle 30kDa PEG. This modification results in a lower affinity for theEPOreceptor but an increased half-life (t1/2 of 134 hours compared to 8.5 hours for epoetin alfa and 26 hours for Aranesp)82.

GlycoPEGylation, successfully applied to Lonquex (lipegfil-grastim), is the combination of a glycoengineering and PEGylationtechnology. Lonquex is granulocyte colony stimulating factor (G-CSF)which has been enzymatically modified with a 20-kDa PEG-sialic acid derivative. To achieve this, G-CSF is expressed in E. coli and the 20-kDa PEG-sialic acid derivative is transferred to the unused natural O-linked glycosylation site with a truncated N-acetylgalactosaminyltransferase isoform64. This approach has also

been applied to, interferon-alpha2b (IFN-α2b), granulocyte/macrophage colony stimulating factor (GM-CSF), and recombinantactivated factors VII, VIII and IX84-87.

Incorporation of unnatural amino acids Another emerging field in protein engineering for the site-specificconjugation of functional moieties to biopharmaceuticals is theincorporation of unnatural amino acids (uAA). The expansion of the genetic code is essentially the recoding of an antisense codon tobiosynthetically incorporate unnatural amino acids into proteinscaffolds88,89. This work was first pioneered in an E.coli system by Shultzand co-workers, where the specificity of the Methanococcus jannaschiityrosyl tRNA synthetase was redirected towards uAAs88,89.

The essential components for the incorporation of uAA’s are anaminoacyl tRNA synthetase (aaRS) that charges a specific tRNA with auAA and an orthogonal tRNA anticodon mutated to recognise anonsense codon e.g. the amber stop codon TAG. The aaRS-tRNA mustbe orthogonal with respect to the expression system – the aaRS must not recognise any host cell tRNA and the tRNA must not beaminoacylated by any host aaRS.

This approach has been utilised in E. coli-, mammalian-, yeast-


PROTEIN EXPRESSION

33. Gotthard K, Kang HA, Gellissen G. Hansenula polymorpha (Pichia angusta): Biology andApplications. Satyanarayana T, Gotthard K (Editors). Yeast Biotechnology: Diversity and Applications, 2009, 47-64

34. Wurm FM. Production of recombinant protein therapeutics in cultivated mammalian cells.Nature Biotechnology, 2004, 22, 1393 – 1398

35. Ghaderi D, Zhang M, Hurtado-Ziola N, Varki A. Production platforms for biotherapeuticglycoproteins. Occurrence, impact, and challenges of non-human sialylation. Biotechnology& genetic engineering reviews, 2012, 28, 147-75.

36. Croset A, Delafosse L, Gaudry J-P, Arod C, Glez L, Losberger, C, Begue D, Krstanovic A,Robert F, Vilbois F, Chevalet L, Antonsson B, Differences in the glycosylation of recombinantproteins expressed in HEK and CHO cells, Journal of Biotechnology, 2012, 161, 336-348

37. Llop E, Gutiérrez-Gallego R, Segura J, Mallorquí J, Pascual JA. Structural analysis of theglycosylation of gene-activated erythropoietin (epoetin delta, Dynepo). AnalyticalBiochemistry, 2008, 383, 243-254

38. Lai T, Yang Y, Ng SK. Advances in Mammalian Cell Line Development Technologies forRecombinant Protein Production. Pharmaceuticals, 2013, 6, 579-603.

39. De Jesus MJ, Wurm FM. Mammalian Cells in Biotech Production. Kayser O, Warzecha H(Editors). Pharmaceutical Biotechnology: Drug Discovery and Clinical Applications, SecondEdition, 2012, 43-57

40. Ausländer S, Fussenegger M. From gene switches to mammalian designer cells: present andfuture prospects. Trends in Biotechnology, 2013, 31, 155–168

41. Basile G, Peticca M. Recombinant Protein Expression in Leishmania tarentolae. MolecularBiotechnology, 2009, 43, 273-278

42. Jørgensen ML, Friis NA, Just J, Madsen P, Petersen SV, Kristensen P. Expression of single-chain variable fragments fused with the Fc-region of rabbit IgG in Leishmania tarentolae.Microbial Cell Factories, 2014, 13:9

43. Sepúlveda S, Valenzuela L, Ponce I, Sierra S, Bahamondes P, Ramirez S, Rojas V,Kemmerling U, Galanti N, Cabrera G. Expression, functionality, and localization ofapurinic/apyrimidinic endonucleases in replicative and non-replicative forms ofTrypanosoma cruzi. Journal of Cellular Biochemistry, 2014, 115: 397-409

44. Taromchi AH, Kazemi B, Mahmazi S, Bandehpour M. Heterologous Expression of Human IL-29 (IFN-λ1) in Iranian Lizard Leishmania. Iranian Journal of Biotechnology,2013, 11, 168-174

45. Niimi T. Recombinant Protein Production in the Eukaryotic Protozoan Parasite Leishmaniatarentolae: A Review. Methods in Molecular Biology, 2012, 824, 307-315

46. Zawada JF, Yin G, Steiner AR, Yang J, Naresh A, Roy SM, DS Gold DS, Heinsohn HG,Murray CJ Microscale to manufacturing scale-up of cell-free cytokine production – a newapproach for shortening protein production development timelines Biotechnology andBioengineering, 2011, 108, 1570 – 1578

47. Runkel L, Meier W, Pepinsky R, Karpusas M, Whitty A, Kimball K, Brickelmaier M,Muldowney C, Jones W, Goelz S,. Structural and functional differences between glycosylatedand non-glycosylated forms of human interferon-beta (IFN-beta). Pharmaceutical research,1998, 15, 641-649

48. Data from www.ema.europa.eu and www.fda.gov

49. Debeljak N, Sytkowski A,. Erythropoietin and erythropoiesis stimulating agents. DrugTesting and Analysis, 2012, 4, 1942-7611

50. Egrie J, Browne J,. Development and characterization of novel erythropoiesis stimulatingprotein (NESP). 2011, British journal of cancer, 84. 3-10

51. Bolt G, Bjelke J, Hermit M, Hansen L, Karpf D, Kristensen C,. Hyperglycosylation prolongsthe circulation of coagulation factor IX. Journal of thrombosis and haemostasis : 2012, 10,2397-2398

52. Ceaglio N, Etcheverrigaray M, Kratje R, and Oggero M,. Novel long-lasting interferon alphaderivatives designed by glycoengineering. Biochimie, 2008, 90, 437-449

53. Lusch A, Kaup M, Marx U, Tauber R, Blanchard V, Berger M. Development and analysis ofalpha 1-antitrypsin neoglycoproteins: the impact of additional N-glycosylation sites on serumhalf-life. Molecular pharmaceutics, 2013, 10, 2616-2629

54. Weenen C, Peña J, Pollak S, Klein J, Lobel L, Trousdale R, Palmer S, Lustbader E, Ogden R,Lustbader J,. Long-acting follicle-stimulating hormone analogs containing N-linkedglycosylation exhibited increased bioactivity compared with o-linked analogs in female rats.The Journal of clinical endocrinology and metabolism, 2004, 89, 5204-5212

55. Jefferis R. Glycosylation as a strategy to improve antibody-based therapeutics. NatureReviews Drug Discovery, 2009, 8, 226-234

56. Solá R, Griebenow K,. Effects of glycosylation on the stability of protein pharmaceuticals.Journal of pharmaceutical sciences, 2009, 98, 1223-1245

57. Satoh M , Iida S, Shitara K,. Non-fucosylated therapeutic antibodies as next-generationtherapeutic antibodies. 2006, 6, 1161-1173

58. Golay J, Da Roit F, Bologna L, Ferrara C, Leusen J, Rambaldi A, Klein C, Introna M.Glycoengineered CD20 antibody obinutuzumab activates neutrophils and mediatesphagocytosis through CD16B more efficiently than rituximab. Blood, 2013, 122, 3482-3491

59. Zhou Q, Stefano J, Manning C, Kyazike J, Chen B, Gianolio D, Park A, Busch M, Bird J,Zheng X, Simonds-Mannes H, Kim J, Gregory R, Miller R, Brondyk W, Dhal P, Pan C,. Site-specific antibody-drug conjugation through glycoengineering. Bioconjugate chemistry, 2014,25, 510-520

60. Walsh G, Jefferis R. Post-translational modifications in the context of therapeutic proteins.Nature biotechnology, 2006, 24, 1241-1252

61. Curran MP, McCormack PL. Methoxy Polyethylene Glycol-Epoetin Beta. Drugs, 2008, 68, 1139 – 1156

62. Alconcel SNS, Baas AS, Maynard HD. FDA-approved poly(ethylene glycol)–proteinconjugate drugs. Polymer Chemistry, 2011, 2, 1442-1448

63. Stead RB, Lambert J, Wessels D, Iwashita JS, Leuther KK, Woodburn KW, Schatz PJ,Okamoto DM, Naso R, Duliege AM. Evaluation of the safety and pharmacodynamics ofHematide, a novel erythropoietic agent, in a phase 1, double-blind, placebo-controlled, dose-escalation study in healthy volunteers. Blood, 2006,108, 1830-1834

64. Mahlert F, Schmidt K, Allgaier H, Liu SP. Rational Development Of Lipegfilgrastim, a NovelLong-Acting Granulocyte Colony-Stimulating Factor, Using Glycopegylation Technology.Blood, 2013, 122, 4853

65. Sherman MR, Saifer MGP, Perez-Ruiz F. PEG-uricase in the management of treatment-resistant gout and hyperuricemia.Advanced Drug Delivery Reviews, 2008, 60, 59-68

66. Sundy JS, Ganson NJ, Kelly, SJ, Scarlett EL, Rehrig CD, Huang W, Hershfield MS.Pharmacokinetics and pharmacodynamics of intravenous PEGylated recombinantmammalian urate oxidase in patients with refractory gout. Arthritis & Rheumatism, 2007, 56, 1021-1028

References continued from page 16

cells and cell free platforms87-97. Current restrictions associated with uAA incorporation include low overall product yield, the efficiency of the uAA incorporation and the subsequent conjugation effici-ency. Despite this, there have been a number of successful examples of conjugated pharmaceutical proteins developed using thismethodology, especially for the generation of antibody-drugconjugates93,95-100. The pharmaceutical company Ambrx has recentlypublished the production of Antibody Drug Conjugates in CHO cells using uAA incorporation via their EuCODE technology86. Expression yields for this system were on the 1g/L scale with an overall conjugation yield of 95%.

Concluding remarksOver the last 20 years more complex expression systems have come intouse. With rapid developments in post-translational engineering andstrain development to produce even better defined products, fasterapproval of biopharmaceuticals can be expected, especially if transientcell expression and CFPS production methods are approved. After therevolution of modern molecular biology to the field of bio -pharmaceuticals it is time for a PTM revolution via synthetic biology andchemical conjugations.

PROTEIN EXPRESSION


67. Kling J. PEGylation of Biologics. BioProcess International, 2013, 11, 34–43

68. Möller I, Thomas A, Geyer H, Schänzer W, Thevis M. Synthesis, characterisation, and massspectrometric detection of a pegylated EPO‐mimetic peptide for sports drug testing purposes.

69. Wrighton NC, Farrell FX, Chang R, Kashyap AK, Barbone FP, Mulcahy LS, Johnson DL,Barrett RW, Jolliffe LK, Dower WJ. Small peptides as potent mimetics of the proteinhormone erythropoietin. Science, 1996, 273, 458-64.

70. Ng, EWM, Shima DT, Calias P, Emmett T. Cunningham-Jr ET, Guyer DR. Adamis AP.Pegaptanib, a targeted anti-VEGF aptamer for ocular vascular disease. Nature Reviews DrugDiscovery 5, 123-132

71. Simona J, Menci K, Vladka GP. PEGylation of therapeutic proteins. Biotechnology Journal,2010, 5, 113–128

72. Pradhananga S, Wilkinson I, Ross RJM. Pegvisomant: structure and function. Journal ofMolecular Endocrinology, 2002, 29, 11-14

73. Crawford J. Pegfilgrastim: the promise of pegylation fulfilled. Annals of Oncology, 2003, 14, 6-7

74. Lai L, Hui CK, Leung N, Lau GK. Pegylated interferon alpha-2a (40 kDa) in the treatment ofchronic hepatitis B. International Journal of Nanomedicine, 2006, 1, 255–262

75. Jevševar S, Kunstelj M, Porekar V. PEGylation of therapeutic proteins. BiotechnologyJournal, 2010, 5

76. See www.bolderbio.com

77. See www.creativepegworks.com

78. Cong Y, Pawlisz E, Bryant P, Balan S, Laurine E, Tommasi R, Singh R, Dubey S, Peciak K,Bird M, Sivasankar A, Swierkosz J, Muroni M, Heidelberger S, Farys M, Khayrzad F,Edwards J, Badescu G, Hodgson I, Heise C, Somavarapu S, Liddell J, Powell K, Zloh M,Choi J, Godwin A, Brocchini S,. Site-specific PEGylation at histidine tags. Bioconjugatechemistry, 2012, 23, 248-263

79. Harris J, Chess R. Effect of PEGylation on pharmaceuticals. Nature reviews. Drug discovery,2003, 214-221

80. Fishburn C. The pharmacology of PEGylation: balancing PD with PK to generate noveltherapeutics. Journal of pharmaceutical sciences, 2008, 97, 4167-4183

81. Kling J. PEGylation of Biologics. BioProcess International, 2013, 11, 34–43

82. Curran M, McCormack P. Methoxy polyethylene glycol-epoetin beta: a review of its use in the management of anaemia associated with chronic kidney disease. Drugs, 2008, 68, 1139-1156

83. Alconcel S, Bass A, and Maynard H. FDA-approved poly(ethylene glycol)–protein conjugatedrugs. Polymer chemistry, 2011, 2, 1442-1448

84. Golor G, Bensen-Kennedy D, Haffner S, Easton R, Jung K, Moises T, Lawo J-P, Joch C,Veldman A,. Safety and pharmacokinetics of a recombinant fusion protein linkingcoagulation factor VIIa with albumin in healthy volunteers. Journal of thrombosis andhaemostasis, 2013, 11, 1977-1985

85. Negrier C, Knobe K, Tiede A, Giangrande P, Møss J,. Enhanced pharmacokinetic propertiesof a glycoPEGylated recombinant factor IX: a first human dose trial in patients withhemophilia B. , 2011, 118, 2695-2701

86. Stennicke H, Kjalke M, Karpf D, Balling K, Johansen P, Elm T, Øvlisen K, Möller F,Holmberg H, Gudme C, Persson E, Hilden I, Pelzer H, Rahbek-Nielsen H, Jespersgaard C,Bogsnes A, Pedersen A, Kristensen A, Peschke B, Kappers W, Rode F, Thim L, Tranholm M,Ezban M, Olsen E, Bjørn S,. A novel B-domain O-glycoPEGylated FVIII (N8-GP)demonstrates full efficacy and prolonged effect in hemophilic mice models. Blood, 2013,121, 2108-2116

87. DeFrees S, Wang Z, Xing R, Scott AE, Wang J, Zopf D, Gouty DL, Sjoberg ER,Panneerselvam K, Brinkman-Van der Linden ECM, Bayer RJ, Tarp MA, Clausen H,.GlycoPEGylation of recombinant therapeutic proteins produced in Escherichia coli.Glycobiology, 2006, 16, 833-843

88. Wang L, Brock A, Herberich B, Schultz P,. Expanding the genetic code of Escherichia coli.Science, 2001, 292, 498-500

89. Young T, Schultz P. Beyond the canonical 20 amino acids: expanding the genetic lexicon. The Journal of biological chemistry, 2010, 285, 11039-11044

90. Chin J, Cropp T, Anderson J, Mukherji M, Zhang Z, Schultz P,. An expanded eukaryoticgenetic code. Science, 2003, 301, 964-967

91. Sakamoto K, Hayashi A, Sakamoto A, Kiga D, Nakayama H, Soma A, Kobayashi T,Kitabatake M, Takio K, Saito K, Shirouzu M, Hirao I, Yokoyama S,. Site-specificincorporation of an unnatural amino acid into proteins in mammalian cells. Nucleic acidsresearch, 2002, 30, 4692-4699

92. Kowal A, Kohrer C, RajBhandary U,. Twenty-first aminoacyl-tRNA synthetase-suppressortRNA pairs for possible use in site-specific incorporation of amino acid analogues intoproteins in eukaryotes and in eubacteria. Proceedings of the National Academy of Sciences ofthe United States of America, 2001, 2268-2273

93. Zimmerman E, Heibeck T, Gill A, Li X, Murray C, Madlansacay M, Tran C, Uter N, Yin G,Rivers P, Yam A, Wang W, Steiner A, Bajad S, Penta K, Yang W, Hallam T, Thanos C, Sato A.Production of site-specific antibody-drug conjugates using optimized non-natural aminoacids in a cell-free expression system. Bioconjugate chemistry , 2014, 25, 351-361

94. Goerke A, Swartz J. High-level cell-free synthesis yields of proteins containing site-specificnon-natural amino acids. Biotechnology and bioengineering, 2009, 400-416

95. Ozawa K, Loscha K, Kuppan K, Loh C, Dixon N, Otting G,. High-yield cell-free proteinsynthesis for site-specific incorporation of unnatural amino acids at two sites. Biochemicaland biophysical research communications, 2012, 418, 652-656

96. Jackson D, Atkinson J, Guevara C, Zhang C, Kery V, Moon S, Virata C, Yang P, Lowe C,Pinkstaff J, Cho H, Knudsen N, Manibusan A, Tian F, Sun Y, Lu Y, Sellers A, Jia X, Joseph I,Anand B, Morrison K, Pereira D, Stover D. In vitro and in vivo evaluation of cysteine and sitespecific conjugated herceptin antibody-drug conjugates. PloS one, 2014, 9, 34-45

97. Panowksi S, Bhakta S, Raab H, Polakis P, Junutula J. Site-specific antibody drug conjugatesfor cancer therapy. mAbs, 2014, 6, 34-45

98. See www.allozyne.com

99. See www.ambrx.com

100.Tian F, Lu Y, Manibusan A, Sellers A, Tran H, Sun Y, Puong T, Barnett R, Hehli B, Song F,DeGuzman M, Ensari S, Pinkstaff J, Sullivan L, Biroc S, Cho H, Schultz P, DiJoseph J,Dougher M, Ma D, Dushin R, Leal M, Tchistiakova L, Feyfant E, Gerber H, Sapra P. Ageneral approach to site-specific antibody drug conjugates. Proceedings of the NationalAcademy of Sciences of the United States of America, 2014, 111, 1766-1771

Marco Casteleijn is working at the Centre for DrugResearch at the Faculty of Pharmacy of the University ofHelsinki in Finland. He obtained his Ba in Life Sciences inUtrecht, the Netherlands. Before his PhD, Marco was TestSupervisor and Researcher at the National Institute for PublicHealth and the Environment at the Dutch drug regulatoryoffices for biological drug release, and worked as a

technician for a fresh water provider (microbiology and analytical chemistry)and in the cosmetics and food industry. Marco obtained his Msc inBiochemistry and his PhD in Bioprocess Engineering at the University ofOulu in Finland where he worked in protein engineering projects on industrialenzymes. He is currently working on pharmaceutical proteins: developmentand delivery. He has published several peer review articles on proteinengineering, bioprocess development, and industrial enzymes. In addition,Marco has a background in quality assurance, was a board member of theBiocenter Oulu graduate school, and is on the scientific advisory board of aGerman Biotech company. Email: [email protected].

Dominique Richardson graduated with a Master ofChemistry from the University of Durham in 2009. Shesubsequently undertook her PhD studies in proteinbiochemistry at the University of Manchester with Prof.Sabine Flitsch. Upon completing this in 2013, she joinedthe University of Helsinki where she currently works as apostdoctoral researcher with Prof. Arto Urtti on thedevelopment of a ‘capture and release’ cell-free platform for the expressionand screening of pharmaceutical proteins.

OverviewEuropean Pharmaceutical Review and Fraunhofer ScreeningPort are pleased to present another unique practical workshop coveringthe development of cell based assays for screening.

Taking place over three days at the Fraunhofer ScreeningPort facility in Hamburg, the workshop will offer you the chance toparticipate in practical sessions using the latest technology available from Biolog, PerkinElmer and Tecan.

This is a must-attend event for anyone in the drug discovery industry to learn about cell based assays for screening technologiesand discover what they can do for your company or laboratory.

Package includes:� 3 days practical workshop using the latest technology available

from the top screening equipment / reagent vendors in thepharmaceutical industry

� All supporting workshop materials� 3 nights’ accommodation at the Radisson Blu Hotel in Hamburg� Daily breakfast, lunch and refreshments� Welcome dinner at Hamburg’s renowned Henssler & Henssler restaurant� Optional city tour

Pricing€1800 – Academic / Research Institution€3000 – Pharmaceutical Industry

Find out more and register: www.europeanpharmaceuticalreview.com/screening-workshop

In association with:

Details3-day practical workshopVenue: Fraunhofer ScreeningPort, Hamburg, GermanyDate: 19-21 November, 2014

WORKSHOP PREVIEW


© Sofiaw

orld / Shutterstock.comCell based assays forscreening workshopAccess the latestcell based assaysfor screeningtechnologies

Organised by:

The usual mathematical relationship used for multivariate calibrationwith spectroscopic data is

Equation 1: y = Xb + e

where y denotes an m x 1 vector of quantitative information for theanalyte (the API content in this case), m is the number of samples, X symbolises an m x n matrix of spectra measured over n wavelengths,b signifies an n x 1 model vector, and e represents the m x 1 vector ofnormally distributed errors with mean zero and covariance matrix σ2I

with I being the m x m identity matrix13,14. Assuming a good experimental

design and outlier removal, the first step in multivariate calibration is toestimate b, by b

^ = X+y where X+ is a generalised inverse of X.Mathematically, the solution to Equation 1 can be expressed asdetermining a b that satisfies the expression

where the double brackets subscripted with 2 denotes the vector L2

norm (2-norm, Euclidian norm) and measures the magnitude (size) ofthe vector. Once a b^ is determined, it is then used to predict newsamples by y=xTb

^ where the superscript T signifies the matrix algebratranspose operation and the hat indicates estimated values. The

In the pharmaceutical industry, it is necessary to control, in a tight range, the active pharmaceutical ingredient (API)content of products, e.g., tablets or other powder blends. Thus, the API content needs to be continuously monitored.Preferably, analysis for the API content should be in-line (on site) allowing rapid and efficient quality control. It is well documented that spectroscopic methods, such as near-infrared (NIR) and Raman, in conjunction withmultivariate calibration processes, can meet these goals under controlled conditions1-12.

MULTIVARIATE DATA ANALYSIS


© P

hoto

bank

gal

lery

/ Sh

utte

rsto

ck.c

om

The flexibility ofregularisation processesfor multivariate calibration maintenance

John H. KalivasIdaho State University

chemical, physical, instrumental, and environmental conditionscaptured by X and y and used to form b^ shall henceforth be referred toas the primary conditions.

If X does not properly span the conditions expected in futureproduction line products to be predicted with the estimated primarycalibration model vector b^, then predictions of the API content will be inerror. Specifically, calibration (reference) samples used to form amultivariate calibration model must span the variations in thechemical, physical, instrumental, and environmental conditionsexpected in future production line products. This type of globalcalibration is difficult to accomplish as measurement and sampleconditions in the production line will inevitably deviate from thosespanned by the original primary calibration samples used is X and y. For example, the current primary calibration can fail due to thecalibrated API being lower or higher than the amounts in the calibrationy or new spectrally responding chemical constituents appear in X.Depending on the instrument and sample type, other chemical,physical, and environmental influences can cause new spectral featuresto appear. These include changes in viscosity, particle size, surfacetexture, pH, temperature, humidity, and pressure. Instrumental effectscan also cause a current calibration to fail and these include drift andrepairing the instrument with a new source, detector, or othercomponent. Lastly, a calibration model developed on a primaryinstrument(s) may need to be used to predict the API content from aspectrum measured on a different instrument. Thus, mechanisms areneeded to update the primary model to include new chemical, physical,instrumental, and/or environmental effectsnot in the current calibration domain. If acalibration model is not adapted to newconditions, it will not accurately predict APIconcentrations (or other calibrated chemical orphysical pharmaceutical attributes15,16). For the remainder of this article,any new condition(s) not present in the primary conditions shall bereferred to as the secondary condition(s).

An abundance of processes have been presented in order toaccomplish calibration maintenance, also referred to as calibrationtransfer or standardisation17-56. Four fundamental strategies exist. One is the global modeling approach previously described. This processis challenging to realise due to the large number of samples needed to span all potential future conditions and respective API referencevalues must be determined for each sample. Determining API reference values is time consuming and costly.

As a way to allow global modeling, a second approach to calibrationmaintenance is to incorporate spectral preprocessing methods such asfinite impulse response filters, multiplicative signal correction,derivatives, wavelength selection, mean centering, and orthogonalcorrections28,29. The goal of these approaches is to form a model robustto both primary and secondary conditions.

A third approach is adjusting sample spectra measured in newsecondary conditions to appear as if measured in the primary conditionthereby allowing API content prediction with the primary calibrationmodel. With this strategy, a small set of standardisation (transfer,maintenance) samples are measured in the primary condition at thesame time the full calibration set is measured. This smallstandardisation set must be stable and available for measuring in

future secondary conditions. However, it is not always possible to measure the same samples in the primary and secondary con-ditions. Additionally, this process is restricted to situations that modify spectra due to wavelength shifts, intensity changes, and/orbaseline offsets and not useable when new sample based variances arise. Recently, an orthogonal adjustment in combinationwith spectral transformation was developed (dynamic orthogonalprojection) that eliminated the requirement of the same samples being measured in the original primary calibration and second-ary conditions30.

The fourth strategy, and the emphasis of this article, is to updatethe primary model. Various approaches exist to accomplish this goal31-52.One process involves augmenting the original calibration set withsecondary calibration samples spanning the new spectral variances. Inthis approach, Equation 1 on page 21 is written as (ignoring the e term):

Equation 2:

where M is an s x n matrix of spectra for the s samples measured in the new secondary conditions at the same n wavelengths used to measure the primary samples in X. Reference values for the APIcontent are augmented to y as yM . If the number of secondary samplesis large, then essentially a full recalibration is being performed with nogain in efficiency. For example, an efficient approach for APIdeterminations in tablets generated in full production is to first form tablets in a laboratory setting (primary condition) that span

some simple tablet variances. The goal is toupdate this ‘golden’ primary model with just afew new samples measured in the fullproduction secondary conditions. However, ifthe number of samples is small, then the

updated model vector will be biased towards the primary condition dueto the majority of the samples spanning the primary condition.

With regularisation processes such as Tikhonov regularisation (TR)40-47 or recursive partial least squares (PLS)48-52 a weighing scheme isused for model updating. For TR, Equation 2 becomes

Equation 3:

where η is a tuning parameter (0≤η) that provides numerical stability tothe inverse operation for solution of b, λ weights the secondarycondition samples (0≤λ), I denotes the identity matrix and 0 is therespective zero vector. Mathematically, the solution to Equation 3 canbe expressed as

This process has been successfully used with NIR data to model updatelaboratory prepared tablets to predict API content tablets obtained in afull production44. In other non-pharmaceutical NIR data sets, TR hasbeen effective in updating a primary model formed at one temperatureto predict at new temperatures as well as updating a primary modelformed on one instrument to predict sample analytes from spectrameasured on another instrument40-42. Most recently, TR was used to



An abundance of processes have been presented in order to accomplish

calibration maintenance

update a model formed to predict sunflower oil adulteration of extravirgin olive oil samples obtained from one geographic region to predictsamples from another geographic region43.

The 0 and ηI terms can be removed from Equation 3 on page 22 andthe resulting equation could be solved by PLS where λ is now tuned inconjunction with the PLS latent variables (LVs) instead of η. In recursivePLS, the weight tuning parameter λ is put on the primary calibrationdata and hence, this larger set of samples is down weighted48-52.

Several other TR type processes have been developed andevaluated to accomplish model updating41-43,45-47 including solution to

that uses an L1 (1-norm) causing the updated model to be sparse(wavelengths are selected). These processes provide model updatingand wavelength selection simultaneously. A general form of TR typeregularisations is satisfying the condition

where a, b, and c are typically set for L1 and/or L2 processes. Two specificvariants are in one case with a = b = 2, yL = 0, λ = 0, and L set to aderivative operator to form smoothed regression vectors in the primaryconditions and robust to new secondary conditions53. The second TRvariation is a modification such that reference samples are no longerneeded. Other approaches with no referencesamples have been developed, but theseprocesses do not include spectral weighing54-56.The regularisation algorithm with no referencesamples satisfies

45,46

In this expression, ka represents a spectrum of the analyte as a purecomponent with concentration ya and N symbolises spectra of sampleswithout the API and hence, the corresponding concentrations of thesenon-analyte samples are zero. For an API, ya = 1. In the pharmaceuticalindustry, obtaining samples without the API is not difficult. Theflexibility of this TR type approach allows including reference samples,if such samples are available, with N. Thus, it is possible to calibrate andmodel update with or without reference samples.

The basis of the TR variant with no reference samples assumes alinear Beer-Lambert law type relationship for each measured spectrumx. In this case, x can be expressed as

Equation 4:

where yN and KN signify interferent concentrations and respective non-analyte spectra as rows in KN, and r denotes random spectral noise. The non-analyte spectra in KN can be pure component interferentspectra as well as spectra representing instrumental and/orenvironmental sources affecting x such as scatter, baseline shifts,

background, temperature, etc., (all spectral sources for x not due to theanalyte). To simplify, spectra in KN are scaled by the respectivequantities in yN, and Equation 4 becomes

Equation 5:

where the 1 represents a vector of ones with as many ones as there arespectra in N. Prediction for ya, expressed as ya, is computed bymultiplying x in Equation 5 by an estimated model vector b^ written as

Equation 6:

Based on Equation 6, three conditions must be satisfied in order toobtain the error-free prediction ya=ya. These conditions are: 1. kT

ab^=1, 2.

Nb^=1 (orthogonality of the model vector to the non-analyte

information), and 3. (orthogonality and/or low model complexity).Unfortunately, not all three conditions can be simultaneously satisfiedand a compromise is needed to form the final model vector. Identifyingmodel vectors satisfying

balances the three conditions.For the regularisation processes so far described in this article, only

one regression vector is estimated. This regression vector (model) isdetermined such that a trade-off is balanced between modelling the

primary and secondary conditions. In otherwords, the new model vector balancespredicting samples from both the primary andsecondary condition. Under current study in

our laboratory is developing regularisation processes that actually formtwo model vectors from the primary and secondary data usingminimisation expressions similar to those presented in this article.

To date, tablet data for API content have been the most difficult to work with in our laboratory as several factors cause the need toupdate the primary model. Specifically, principal component analysis of tablets typically reveal that there are batch and tablet effects. In our present work, only one weight is used to update all the secondary conditions represented in M or N. Future work involves usingdifferent tuning parameters to separately weight tablet types andbatches. This is difficult to accomplish as additional tuning parameterswill have to be determined. It is hopeful that advancing regularisationsprocesses allowing two model vectors to be formed will help alleviate this concern.

For References, see page 24



Dr. John H. Kalivas completed his chemistry doctoratefrom the University of Washington in 1982 and joined IdahoState University in 1985. He is author or co-author of over100 papers, book chapters, and books. He serves as Editorfor the Journal of Chemometrics and Applied Spectroscopyand on several Editorial Boards.

Principal component analysis of tablets typically reveal that there

are batch and tablet effects



1. Hu, Y, Erxleben, A, Ryder, AG, McArdle, P (2010) Quantitative analysis of sulfathiazolepolymorphs in ternary mixtures by attenuated total reflectance infrared, near-infrared andRaman spectroscopy, J. Pharm. Biomed. Anal. 2010, 53, 412-420.

2. Blanco, M, Villarroya, I (2002) NIR spectroscopy: a rapid-response analytical tool, TrendsAnal. Chem. 2002, 21, 240-250.

3. Ciurczak, EW, Dremen, J (2010) Pharmaceutical and Medical Applications of Near-InfraredSpectroscopy, CRC Press, Boca Raton, Florida, 2010.

4. Menezes, JC, Ferreira, AP, Rodrigues, LO, Brás, LP (2009) Chemometrics role within thePAT context: examples from primary pharmaceutical manufacturing, in: Brown, SD, Tauler,R, Walczak, B (Eds-in-Chief), Comprehensive Chemometrics: Chemical and BiochemicalData Analysis, Elsevier, Amsterdam, The Netherlands, 2009.

5. Rodionova, OY, Sokovikov, YV, Pomerantsev, AL (2009) Quality control of packed rawmaterials in pharmaceutical industry, Anal. Chim. Acta 2009, 642, 222-227.

6. Blanco, M, Bautista, M, Alcalá, M (2008) Preparing calibration sets for use inpharmaceutical analysis by NIR spectroscopy, J. Pharm. Sci. 2008, 97, 1236-1245.

7. Zheng, Y, Lai, X, Bruun, SW, Ipsen, H, Larsen, JN, Løwenstein, H, Søndergaard, I,Jacobsen, S (2008) Determination of moisture content of lyophilized allergen vaccines byNIR spectroscopy , J. Pharm. Biomed. Anal. 2008, 46, 592-596.

8. Roggo, Y, Chalus, P, Maurer, L, Lema-Martinez, C, Edmond, A, Jent, N (2007) A review ofnear infrared spectroscopy and chemometrics in pharmaceutical technologies, J. Pharm.Biomed. Anal. 2007, 44, 683-700.

9. Cogdill, RP, Drennen III, JK (2005) Near infrared spectroscopy in the pharmaceuticalindustry, NIR News 2005, 23-26.

10. Bakeev, KA (2005) Process Analytical Technology: Spectroscopic Tools andImplementation Strategies for the Chemical and Pharmaceutical Industries, BlackwellPublishing, Oxford, 2005.

11. Freitas, MP, Sabadin, A, Silva, LM, Giannotti, FM, do Couto, DA, Tonhi, E, Medeiros, RSCoco, GL, Russoand, VFT, Martins, JA (2005) Prediction of drug dissolution profiles fromtablets using NIR diffuse reflectance spectroscopy: A rapid and nondestructive method , J. Pharm. Biomed. Anal. 2005, 39, 17-21.

12. Dyrby, M, Engelsen, SB, Nørgaard, L, Bruhn, M, Lundsberg-Nielsen, L (2002)Chemometric quantitation of the active substance3 (containing C≡N) pharmaceutical tabletusing near-infrared (NIR) transmittance and NIR FT-IR Raman spectra, Appl. Spectrosc.2002, 56, 579-585.

13. Næs, T, Isaksson, T, Fern, T, Davies, T (2002) A User Friendly Guide to MultivariateCalibration and Classification, NIR Publications, Chichester, 2002.

14. Kalivas JH (2009) Calibration methodologies, in: Brown, SD, Tauler, R, Walczak, B (Eds-in-Chief), Comprehensive Chemometrics: Chemical and Biochemical Data Analysis,Elsevier, Amsterdam, The Netherlands, 2009, 1–32.

15. Xiang, D, Konigsberger, M, Wabuyela, B, Hornung, K, Cheney, J (2009) Development ofrobust quantitative methods of near-infrared spectroscopy for rapid pharmaceuticaldetermination of content uniformity in complex tablet matrix, Analyst 2009, 134, 1405-1415.

16. Igne, B, Talwar, S, Drennen III, JK, Anderson, CA (2011) Improvement if pharmaceuticalnear infrared calibrations by empirical target distribution optimization, J. Near InfraredSpectrosc. 2011, 19, 1-14.

17. T. Fearn, T (2001) Standardization and calibration transfer for near infrared instruments: A review, J. Near Infrared Spectrosc. 2001, 9, 229-244.

18. Feudale, RN, Woody, NA, Tan, H, Myles, AJ, Brown, SD, Ferré, J (2002) Transfer ofmultivariate calibration models: a review. Chemom. Intell. Lab. Syst. 2002, 64, 181-192.

19. Cogdill, RP, Anderson, CA, Drennen III, JK (2005) Process analytical technology casestudy, Part III: Calibration monitoring and transfer, AAPS PharmSciTech 2005, 6, E284-E297.

20. Brown, SD (2009) Transfer of multivariate calibration models, in: Brown, SD, Tauler, R,Walczak, B (Eds-in-Chief), Comprehensive Chemometrics: Chemical and BiochemicalData Analysis, Elsevier, Amsterdam, The Netherlands, 2009.

21. Cogdill, RP, Herkert, T, Anderson, CA, Drennen III, JK (2007) Synthetic calibration forefficient mentod development: analysis of tablet API concentration by near-infraredspectroscopy, J. Pharm. Innov. 2007, 2, 93-105.

22. Du, W, Chen, Z, Zhong, L, Wang, S, Yu, R, Nordon, A, Littlejohn, D, Holden, M (2011)Maintaining the predictive abilities of multivariate calibration models by spectral spacetransformation, Anal. Chim. Acta 2011, 690, 64-70.

23. Shi, Z, Igne, B, Bondi Jr., RW, Drennen III, JK, Anderson, CA (2012) Calibration transferfrom pharmaceutical powder mixtures to compacts using prediction augmented classicalleast squares (PACLS) method, Appl. Spectrosc. 2012, 66, 1075-1081.

24. Igne, B, Roger, J, Roussel, S, Bellon-Maurel, V, Hurburgh, CR (2009) Improving thetransfer of near infrared prediction models by orthogonal methods, Chemom. Intell. Lab.Syst. 2009, 99, 57-65.

25. Wangdong, N, Brown, SD, Man, R (2010) Data fusion in multivariate calibration transfer,Anal. Chim. Acta 2010, 661, 133-142.

26. Wangdong, N, Brown, SD, Man, R (2010) Stacked PLS for calibration transfer withoutstandards, J. Chemom. 2010, 25, 130-137.

27. DiFoggio, R (2005) Desensitizing models using covariance matrix transforms or counter-balanced distortions, J. Chemom. 2005, 19, 203-215.

28. Anderson, CE, Kalivas, JH (1999) Fundamentals of calibration transfer through ProcrustesAnalysis, Appl. Spectrosc. 1999, 53, 1268-1276.

29. Kalivas, JH (2008) Learning from Procrustes analysis to improve multivariate calibration, J. Chemom. 2008, 22, 227-234.

30. Zeaiter, M, Roger, JM, Bellon-Maurel, V (2006) Dynamic orthogonal projection. A newmethod to maintain the on-line robustness of multivariate calibrations. Application to NIR-based monitoring of wine fermentations, Chemom. Intell. Lab. Syst. 2006, 80, 227-235.

31. M.O. Westerhaus, Improving repeatability of NIR calibrations across instruments, in: R. Briston, N. Bartiaux-Thill (Eds), Proceedings of the Third International Near InfraredSpectroscopy Conference, Agriculture Research Centre Publishing, Gembloux, Belgium,1991, pp 671-674.

32. Kramer,KE, Small, GW (2007) Blank augmentation protocol for improving the robustnessof multivariate calibrations, Appl. Spectrosc. 2007, 61, 497-506.

33. Sulub, Y, Small, GW (2007) Spectral simulation methodology for calibration transfer ofnear-infrared spectra, Appl. Spectrosc. 2007, 61, 406-413.

34. Condolfi, A, Massart, DL (2000) Model updating for the identification of NIR spectra froma pharmaceutical excipient, Appl. Spectrosc. 2000, 54, 48-53.

35. Riley, MR, Arnold, MA, Murhammer, DW (1998) Matrix-enhanced calibration procedure for multivariate calibration with near-infrared spectra, Appl. Spectrosc. 1998, 52,1339-1347.

36. Wehlburg, CM, Haaland, DM, Melgaard, DK, Martin, LE (2002) New hybrid algorithm formaintaining multivariate quantitative calibrations of a near-infrared spectrometer. Appl.Spectrosc. 2002, 56, 605-614.

37. Wehlburg, CM, Haaland, DM, Melgaard, DK (2002) New hybrid for transferringmultivariate quantitative calibrations of intra-vendor near-infrared spectrometers. Appl.Spectrosc. 2002, 56, 877-886.

38. Stork, CL, Kowalski, BR (1999) Weighting schemes for updating regression models – a theoretical approach. Chemom. Intell. Lab. Syst. 1999, 48, 151-166.

39. Capron, X, Walczak, B, de Noord, OE, Massart, DL (2005) Selection and weighting ofsamples in multivariate regression model updating. Chemom. Intell. Lab. Syst. 2005, 76,205-214.

40. Kalivas, JH, Siano, GS, Andries, E, Goicoechea, HC (2009) Calibration maintenance andtransfer using Tikhonov regularisation approaches, Appl. Spectrosc. 2009, 63, 800-809.

41. Kunz, MR, Kalivas, JH, Andries, E (2010) Model updating for spectral calibrationmaintenance and transfer using 1-norm variants of Tikhonov regularisation, Anal. Chem.2010,89, 3642-3649.

42. Kunz, MR, Ottaway, J, Kalivas, JH, Andries, E (2009) Impact of standardization sampledesigns on Tikhonov regularisation variants for spectroscopic calibration maintenance andtransfer, J. Chemom. 2009, 24, 218-229.

43. Kunz, MR, Ottaway, J, Kalivas, JH, Georgiou, CA, Mousdis, GA (2011) Updating asynchronous fluorescence spectroscopic virgin olive oil adulteration calibration to a newgeographical region, J. Agric. Food Chem. 2011, 59, 1051-1057.

44. Farrell, JA, Higgins, K, Kalivas, JH (2012) Updating a near-infrared multivariate calibrationmodel formed with lab-prepared pharmaceutical tablet types to new tablet types in fullproduction, J. Pharm. Biomed. Anal. 2012, 61, 114-121.

45. Ottaway, J, Farrell, JA, Kalivas, JH (2013) Spectral multivariate calibration without laboratory prepared or determined reference analyte values, Anal. Chem. 2012, 85,1509-1516

46. Kalivas, JH, Georgiou, CA, Moira, M, Tsafaras, I, Petrakis, E, Mousdis, GA (2014) Foodadulteration analysis without laboratory prepared or determined reference food adulterantvalues, Food Chem. 2014, 148, 289-293.

47. Kalivas, JH (2012) Overview of two-norm (L2) and one-norm (L1) Tikhonov regularisationvariants for full wavelength or sparse spectral multivariate calibration models ormaintenance. J. Chemom. 2012, 26, 218-230.

48. Wold, S (1984) Exponentially weighted moving principal components analysis andprojections to latent structures, Chemom. Intell. Lab. Syst. 1984, 23, 149-161.

49. Helland, K, Berntsen, HA, Borgen, OS, Martens, H (1991) Recursive algorithm for partialleast squares. Chemom. Intell. Lab. Syst. 1991, 14, 129-137.

50. Dayal, BS, MacGregor, JF (1997) Recursive exponentially weighted PLS and itsapplications to adaptive control and prediction, J. Proc. Cont. 1997, 7, 169-179.

51. Qin, SJ (1998) Recursive PLS algorithms for adaptive modeling, Computers Chem. Engng.1998, 22, 503-514.

52. Wangdong, N, Tan, SK, Ng, WJ, Brown, SD (2012) Localized, adaptive recursive partialleast squares regression for dynamic system modeling, Ind. Eng. Chem. Res. 2012, 51,8025-8039.

53. Forrest, S, Kalivas, JH (2006) Tikhonov regularisation in standardized and general form formultivariate calibration with application towards removing unwanted spectral artifacts, J. Chemom. 2006, 20, 22-33.

54. Marbach, R (2002) On Wiener filtering and the physics behind statistical modeling, J. Biomed. Optics 2002, 7, 130-147.

55. Marbach, R (2005) A new method for multivariate calibration. J.Near Infrared Spectrosc.2005, 13, 241-254.

56. Boulet, JC, Roger, JM (2010) Improvement of direct calibration in spectroscopy, Anal.Chim. Acta 2010, 668, 130-136.

References

The 2014 event will feature a programme ofscientific presentations, an exhibition areawith around 100 vendor booths, networkingopportunities, poster sessions, Dragons Den,Authors Workshop, Innovation Zone, MediaArea and Careers Zone, and for the first time aseries of Core Technologies Workshops,providing a more informal, interactiveenvironment in which to discuss key issuesand future directions, coordinated by leadersin their fields. There will be eight ScientificSessions altogether, with three new sessionscovering cutting-edge topics: PhenotypicDiscovery & Cellular Imaging; ChemicalInnovation in Lead Discovery; and Neuro -science Drug Targets.

The Scientific Sessions will featurepresentations2 from leading scientists,including the show keynote address from Dr Susan Galbraith, Head of Oncology atAstraZeneca, on ‘Genetic drivers of cancergrowth and resistance mechanisms’. Otherspeakers include: Lorenz Mayr, AstraZeneca;Daniela Gabriel, Novartis; Olli Kallioniemi,FIMM, Helsinki; Stefan Offermans, Max Planck;Dario Neri, ETH, Zurich; Lutz Jermuntas,MedImmune; and Eric Karran, AlzheimersResearch UK.

In partnership with SLAS, this year’sconference will be preceded by a series of oneday short courses3, which will take place onMonday 1 September 2014. The courses arecomplementary to the conference pro -

gramme; their objective is to educate peopleinterested in these fields, providing an in-depth understanding of the topic and acomprehensive overview of the key tech -niques and recent developments. Delivered bydistinguished faculty, these courses address arange of timely issues using real-worldexamples. The courses comprise:

Course 1: Introduction to Laboratory AutomationThis introduction to automation course willprovide a basic overview of when and how tosuccessfully deploy automation within alaboratory environment. The course is tailoredfor managers who want to understand thestrategic and tactical options for automationdeployment. There will be an overview of theprinciples of automation architecture,infrastructure and laboratory informatics.There is no requirement for a workingknowledge of, or experience with, automation.

Course 2: High Content Screening:Instrumentation, Assay Development,Screening, Image and Data AnalysisHigh Content Screening is a powerfultechnology platform for implementingfunctional cell-based assays that allow trulymulti-parametric analysis in the physiologicalcontext of intact cells. This course provides astate-of-the-art overview of the componentsof HCS (instrumentation, reagents, HC assay

development, automated image analysis andmulti-parametric data analysis, and datastandards) together with some showcases ofsmall molecule and RNAi high-contentscreens in industry and academia.

Course 3: Establishing Cell-BasedAssays and Implementing 3D CultureModels for Screening and Drug TestingThis course will describe developing standardprocedures for handling cultured cells to set-up cell-based assays, describe techniques formeasuring cell health and the mechanismsleading to cytotoxicity, and provide anoverview of recent technological advances in3D culture technologies that enable automa -tion-compatible drug testing with morepredictive and biologically relevant assays.

Follow ELRIG on Twitter (@E_LRIG) andLinkedIn (www.linkedin.com/groups/ELRIG-2951734) for updates on this event, and more.The Twitter hashtag for the Drug Discoveryevent is #ELRIGDD14

ELRIG – the European Laboratory Robotics Interest Group – has announced details of the programme for DrugDiscovery 2014. Now in its 8th year, the conference and exhibition is the largest drug discovery meeting in the UK,and is expected to attract over 1,000 delegates. The event provides an opportunity for scientists from all fields ofearly stage drug discovery to network throughout the two days, and to hear world class speakers present on thelatest challenges, opportunities and advances. Registration for the event is free, and delegates can register online1.

SHOW PREVIEW: DRUG DISCOVERY 2014

The largest drug discovery meeting in the UK


Date: 2 – 3 September 2014Location: Manchester CentralConvention ComplexFor more information, please visit www.elrig.org

1. www.elrig.org

2. http://elrig.org/drug-discovery-2014-overview/

3. www.elrig.org/portfolio/slas-short-courses-drug-discovery-2014

References


SPONSORS

29 Reviewing the roles and opportunities for informatics inpharmacovigilance Brittany L. Melton, University of Kansas

32 Laboratory informatics: a wind of change? John Trigg, phaseFour Informatics

Informatics

© d

onfio

re /

Shut

ters

tock

.com

PHARMACEUTICAL HEALTH SCIENCES FOOD ENVIRONMENTAL CHEMICAL MATERIALS

©2014 Waters Corporation. Waters, Empower and The Science of What’s Possible are registered trademarks of Waters Corporation.

Empower® Software is known for enterprise-level power, productivity and MS control.

Empower 3 delivers even more capabilities to hundreds of thousands of users like you with

customizable views, analytics dashboards, plus enhanced mobility and usability. This includes

a flexible QuickStart interface that knows where you are and what you need at all times.

For an unmatched combination of power and personalization, visit waters.com/EMPOWER3

INFORMATICS & CHROMATOGRAPHY

SOFTWARE

CHROMATOGRAPHY SOFTWARE THAT WORKS THE WAY YOU DO.

POWERFUL JUST GOT MORE PERSONAL.

Spontaneous Reporting Systems (SRS) were developed as a relativelycost-effective method for monitoring drug safety throughout the life ofa drug. Clinicians are able to report adverse events through thesesystems as a part of their daily interactions with patients. Such systems

may be voluntary however, leading to under reporting of adverse drugevents (ADEs), and the number of reports submitted makes itcumbersome for an individual to conduct a case-by-case review of thereports and readily identify signals, particularly for rarely used drugs.

The concept of pharmacovigilance is not new. Since the thalidomide tragedies of the early-1960s, countriesworldwide have recognised the need to continually monitor drug safety. In its efforts to guide drug safety practices, the WHO defined pharmacovigilance as ‘the science and activities relating to the detection, assess-ment, understanding, and prevention of adverse effects or any other possible drug-related problems’1. Given the broad scope of pharmacovigilance, it is natural to expect technology to play a role in order to monitor and react to new information in a timely manner. To that end, multiple informatics approaches have been developed to address this need.

IN-DEPTH FOCUS: INFORMATICS


© B

ackg

roun

dSto

re /

Shut

ters

tock

.com

Reviewing the roles and opportunities for informatics inpharmacovigilance

Brittany L. MeltonUniversity of Kansas

Data mining techniques have been developed to streamline the processof signal detection, but these initial algorithms were more likely to misscertain drug-event pairs. These ‘masked’ drug-event pairs requireadditional mining algorithms which remove some drugs from thedatabase to increase the likelihood of detecting masked signals2.Unmasking algorithms have only produced modest improvement inmasked signal detection, while also losing previously identified signalsin the process2. Signal masking is a clearly identified issue in monitoringdrug safety and unfortunately no viable method currently exists forunmasking signals, particularly when there is no prior knowledge of the drug-event pair to drive data mining. This creates an issue when a novel drug-event pair may be present.Biclustering, a statistical method of groupingdrugs that all have the same adverse eventsassociated with them, has been developed foridentifying novel drug-event pairs. Biclusteringallows for different preparations of an activeingredient, as well as related adverse events, tobe grouped together which improves signal detection3. In one study, itwas found that 41% of the identified clusters may contain novel drug-event pairs, but the authors recognised that validating the cluster resultsis difficult without a gold standard, thus limiting the effectiveness ofbiclustering in novel drug-event detection3. Efforts to build an ontologyof Medical Dictionary for Regulatory Activities (MedDRA) have improvedautomated signal detection, but this process can be time consuming4.

While SRS were the original option for pharmacovigilance, hospitalshave been adopting electronic health records (EHRs), which provideanother option for safety monitoring, but the same methods used toidentify signals in SRS do not always work when applied to EHR data.Pharmaceutical companies may not have the same level of access todata when it is in an EHR compared to a SRS, but the data is more likelyto be complete since EHR documentation is not a separate, voluntarysystem. EHR documentation may provide initial indications of a drug

safety concern before the signal would be identified in an SRS due tothis improved and compulsory documentation. Hospitals may usedifferent EHR systems and may customise them to suit their particularneeds thus complicating the ability to consistently extract the samedata from multiple sites. When these challenges can be overcomehowever, there are multiple opportunities for identifying novel drug-event pairs which are not possible when using an SRS. One study usedpharmacovigilance centres to screen non-elective emergencydepartment admissions for ADEs5. This method allowed for population-based incidence reporting, but could misrepresent some drug-eventpairs due to co-medications, and is time intensive without an effective

means of automating data mining5. Naturallanguage processing (NLP) has also been usedto extract safety data from EHRs. NLP is aprocess of text mining to extract datacontained in narratives and literature that isnot accessible through other data miningtechniques. Use of NLP in discharge summaries

has been used to establish feasibility6. This method was able to identifypotential ADEs and is predicted to be able to detect novel drug-eventpairs as well6. NLP has been further refined to exclude drug-event pairswhere an underlying condition was responsible for the adverse event rather than the drug7. The use of NLP to remove false positivesfrom EHRs can reduce the amount of time needed to review possibledrug-event pairs and may further improve the results from other datamining methods7.

Voluntary SRS and mandatory EHRs have separate strengths andlimitations, but both can be used for pharmacovigilance. EHRs oftenhave more complete longitudinal data, but SRS have a greater numberof records and are designed for safety monitoring8. Some techniquesmay be used in both systems to improve signal detection, but this ispredicated on the fact that data is formatted similarly in the two systems, and adding another EHR may reduce the feasibility9.

The Exploring and UnderstandingAdverse Drug Reactions by integra -tive mining of clinical records andbiomedical knowledge (EU-ADR),combines the complete recordsfound in EHRs with the size of SRSdatabases by combining electronichealth records for about 30 millionpatients from eight databases in four countries10. This massivecombined database presents agreater opportunity for pharma -covigilance, but also presents itsown challenges. Despite the size ofthe EU-ADR, rarely used drugs orrarely occurring adverse events maystill not be detectable11. By oneestimate, the EU-ADR would need tobe 10 times larger to reasonablydetect signals for rhabdomyolysis, arare adverse event, for 9% of thedrugs contained within the data -



Molecular fingerprinting allows analysis of medications with a known

adverse event to be compared to other medications to reveal potential

novel drug-event pairs

© C

athe

rine

Lall

/ Shu

tter

stoc

k.co

m

base11. However, as the EU-ADR grows and detection methods evolve,rare events may be detectable for a larger number of drugs. There isalso a need for a gold standard for evaluating signal detection methods.As is the case with SRS, a reference standard is needed to insure newmethods for data mining are able to correctly identify known drug-event pairs as well as avoid negative controls12.

Data mining techniques in health records databases are not theonly opportunity for informatics involvement in pharmacovigilance.Novel drug-event pairs may also be identified through the use ofmolecular fingerprinting; a method of identifying similarities betweendrug molecules and relating those to biological activity13. Molecularfingerprinting allows analysis of medicationswith a known adverse event to be compared toother medications to reveal potential noveldrug-event pairs. This can be done with rare events, such as rhabdomyolysis orpancreatitis, for which there are not enoughevents in a health records database to detect asignal13,14. Additionally, it can be utilised in conjunction with other datamining techniques to improve detection and analysis of ADEs.Molecular fingerprinting can also be used to identify novel drug-druginteractions, another important aspect of pharmacovigilance15,16. Drug-drug interactions can be dangerous or even lethal, and timelyrecognition is essential. These drug interaction profile finger-prints examine the molecular structures of drugs similar to one known to cause an interaction with another drug and relates that topotential biological actions15,16. Unlike methods for data mining drug-event pairs, there are standards for drug-drug interactions, such asDrugBank or Micromedex15.

Identification of drug-event pairs or drug-drug interactions cancome from other less direct methods that use informatics techniques.Two separate methods of text mining have been used to identify noveldrug characteristics by extracting data from MEDLINE or PubMedabstracts17,18. These methods extract drug names along with key

terms related to drug characteristics or adverse events and have beenshown to not only identify drug-event pairs, but also narrow therapeuticindex drugs, inducers or inhibitors, etc.17. These methods can bestandardised through known drug-event pairs found in the literature,but because this is dependent upon published literature, there may bea delay in detecting drug-event pairs due to the peer-review andpublication process18. Other proposed opportunities for pharma -covigilance include using ICD-9 codes or claims data19. The use of ICD-9 codes is limited to severe ADEs and can result in misclassificationof events if they are not coded at the time the event occurs19. Further identification of drug-event pairs may also result from analysis

of laboratory values found in EHR data. By examining laboratory abnormali tiesbetween patients exposed to a drug and thosenot exposed to a drug, an algorithm examiningthat ratio of abnormalities was able toeffectively identify signals in EHRs20.

Pharmacovigilance can benefit from theuse of informatics methods such as data and text mining, howevermany of these methods could be further refined to improve signaldetection. Both data and text mining can be used in health recordsdatabases such as EHRs and SRS, and non-traditional drug safetymonitoring databases including claims data and published abstracts.The foundations for using informatics in pharmacovigilance have beenestablished, but more work is needed to refine and develop thesemethods in order to build algorithms capable of providing optimalresults for drug safety monitoring.



1. World Health Organization. The importance of pharmacovigilance: Safety monitoring ofmedicinal products. 2002.

2. Wang H, Hochberg AM, Pearson RK, et al. An experimental investigation of masking in theUS FDA adverse event reporting system database. Drug Saf. 2010;33(12)1117-33.

3. Harpaz R, Perez H, Chase HS, et al. Biclustering of adverse drug events in FDA’sspontaneous reporting system. Clin Pharacol Ther. 2011;89(2):243-50.

4. Henegar C, Bousquet C, Louët AL, et al. Building an ontology of adverse drug reactions for automated signal generation in pharmacovigilance. Comput Biol Med. 2006;36(7-8):748-67.

5. Schneeweiss S, Gottler M, Hasford J, et al. First results from an intensified monitoringsystem to estimate drug related hospital admissions. Br J Clin Pharmacol. 2001;52(2):196-200.

6. Wang X, Hripcsak G, Markatou M, et al. Active computerized pharmacovigilance usingnatural language processing, statistics, and electronic health records: a feasibility study. J AmMed Inform Assoc. 2009;16(3): 328-37.

7. Haerian K, Varn D, Vaidya S, et al. Detection of pharmacovigilance-related adverse eventsusing electronic health records and automated methods. Clin Pharmacol Ther.2012;92(2):228-34.

8. Coloma PM, Trifirò G, Patadia V, et al. Postmarketing safety surveillance: Where doessignal detection using electronic healthcare records fit into the big picture? Drug Saf.2013;36(3): 183-97.

9. Harpaz R, Vilar S, DuMouchel W, et al. Combing signals from spontaneous reports andelectronic health records for detection of adverse drug reactions. J Am Med Inform Assoc.2013;20(3):413-9.

10. Trifirò G, Fourrier-Reglat A, Sturkenboom MCJM, et al. The EU-ADR project: preliminaryresults and perspective. Stud Health Technol Inform. 2009;148:43-9.

11. Coloma PM, Trifirò G, Schuemie M, et al. Electronic health databases for active drug safetysurveillance: is there enough leverage? Pharmacoepidemiol Drug Saf. 2012;21(6):611-21.

12. Coloma PM, Avillach P, Salvo F, et al. A reference standard for evaluation of methods fordrug safety signal detection using electronic healthcare record databases. Drug Saf.2013;36(1):13-23.

13. Vilar S, Harpaz R, Chase HS, et al. Facilitating adverse drug event detection inpharmacovigilance databases using molecular structure similarity: application torhabdomyolysis. J Am Med Inform Assoc. 2011;18:i73-i80.

14. Vilar S, Harpaz R, Santana L, et al. Enhancing adverse drug event detection in electronichealth records using molecular structure similarity: application to pancreatitis. PLoS One.2012;7(7):e41471.

15. Vilar S, Harpaz R, Uriarte E, et al. Drug-drug interaction through molecular structuresimilarity analysis. J Am Med Inform Assoc. 2012;19(6):1066-74.

16. Vilar S, Uriarte E, Santana L, et al. Detection of drug-drug interactions by modelinginteraction profile fingerprints. PLoS One. 2013;8(3):e58321.

17. Lin FPY, Anthony S, Polasek TM, et al. BICEPP: an example-based statistical text miningmethod for predicting the binary characteristics of drugs. BMC Bioinformatics.2011;12:112.

18. Wang W, Haerian K, Salmasian H, et al. A drug-adverse event extraction algorithm tosupport pharmacovigilance knowledge mining from PubMed citations. AMIA Annu SympProc. 2011;2011:1464-70.

19. Nadkarni PM. Drug safety surveillance using de-identified EMR and claims data: issues andchallenges. J Am Med Inform Assoc. 2010;17(6):671-4.

20. Yoon D, Park MY, Choi NK, et al. Detection of adverse drug reaction signals using anelectronic health records database: comparison of the laboratory extreme abnormality ratio(CLEAR) algorithm. Clin Pharmacol Ther. 2012;91(3):467-74.

References

Brittany Melton is an Assistant Professor of PharmacyPractice at the University of Kansas School of Pharmacy. Her research interests include the design of health care interfaces and the development of CPOEalerts to improve patient safety and reduce user fatigue.

Pharmacovigilance can benefit from the use of informatics methods such asdata and text mining, however many ofthese methods could be further refined

to improve signal detection

As the power of computer technology grew, interest progressivelyturned towards managing and collating laboratory data, and numeroushome-grown systems evolved, demonstrating the capability andcommercial potential, and acting as a precursorto the Laboratory Information ManagementSystems (LIMS) industry. In time, the replace -ment of the traditional paper lab notebook fellwithin the remit of the digital revolution andthe Electronic Laboratory Notebook (ELN) industry was born.Complementing these systems were Scientific Data ManagementSystems (SDMS), which offered centralised organisation of instrument

data files and their associate meta-data. These three ‘industries’ havegradually converged into the field of ‘laboratory informatics’ – a termthat is generally applied to the broad set of tools that comprise

the handling of data and information in theelectronic, or paperless lab.

Throughout the evolution of the laboratoryinformatics industry, the underlying businessdriver was for process efficiency, laboratory

throughput/productivity and error reduction. These criteria con -sistently appeared at the heart of any purchasing justification asindustries sought to gain competitive advantage through cost reduction

We’re only too familiar with the impact of digital technologies in almost every aspect of life. In some domains theimpact has been dramatic, with established industries facing significant change and ‘sink or swim’ decisions. The outcomes have been a mixture of remarkable success stories in some instances, or dismal failures in others. In the laboratory world, the pace of digital change has been relatively leisurely. It has taken about four decades or so to reach a point where a growing number of laboratories can consider themselves to be ‘electronic’ or‘paperless’. From the early days of digital electronics and the evolving capability to convert analogue signals intodigital outputs, data capture, data processing and laboratory automation have all progressed with increasing levels of sophistication.



John TriggphaseFour Informatics

© d

onfio

re /

Shut

ters

tock

.com

Laboratory informatics:a wind of change?

It has taken about four decades or so toreach a point where a growing number

of laboratories can consider themselvesto be ‘electronic’ or ‘paperless’

and time-to-market by the adoption ofdigital systems to replace time-consuming,low-value manual processes. To meet thisneed, the individual informatics toolstherefore focused primarily on theelimination of waste (time, effort, errors) intask-specific functions, with the addedbonus of providing a managementperspective of laboratory performance. The reporting of numerous case studies in the literature and at conferencessupports the conclusion that theinformatics tools clearly deliver againstthese criteria. However, there are otherunderlying business issues that are nowhaving an increasing impact on laboratoryoperations and hence put new demands onlaboratory informatics. Externalisation,innovation, agility, and the need to exploitthe potential of emerging technologies are all having an impact on the labora-tory landscape.

In recent years, the distribution oflaboratory processes across geographicboundaries and third parties (externalisa tion)has become quite common. The benefit to thebusiness is access to the lowest-cost source ofcommodity laboratory functions, and in somecases, the option to tap into external sources ofexpertise to enhance in-house research and development activi-ties.Data and information manage ment pro cesses therefore become

distributed, and present additional challengesin terms of performance, security and accesscontrol. Laboratory informatics systems are ableto meet this business need by providingrelevant capabilities for real-time collaborationand the sharing of laboratory data and

information, with infrastructures and appropriate levels of accesscontrol to ensure adequate IP protection.

The growing number of changes drivenby externalisation, mergers and acquisitions,and other market forces is increasing theneed for organisations to be more flexibleand accommodating of change in theiroperational systems. Consolidating systemsfollowing such business changes can proveto be costly and time-consuming, and itwould seem increasingly wise to take intoaccount, as early as possible in aninformatics project, the ease and extent towhich a candidate system may be recon -figured, or the data be exported andpreserved in other systems.

Historically, a considerable amount ofscientific innovation came about throughserendipity and the investigation of un -expected outcomes of experiments thatseemingly did not work. Nowadays,innovation has evolved into a systematic,industrial process dependent to a largeextent on making sense of existing data,prior knowledge and evidence-baseddecision-making. To a large extent, we’ve



© st

efan

olun

ardi

/ Sh

utte

rsto

ck.c

om

Throughout the evolution of thelaboratory informatics industry, theunderlying business driver was for

process efficiency, laboratorythroughput/productivity and

error reduction

© A

fric

a St

udio

/ Sh

utte

rsto

ck.c

om

picked most of the low-hanging fruit, and are now having to probe fardeeper, with greater levels of uncertainty. The progressive movetowards larger molecules and biologics in the life science industriesbrings by default, larger and more complex data sets. This in turnthrows the emphasis back to the scientist in terms of evaluating theintegrity, authenticity and provenance of data, but also makes demandson the technology in terms of the tools available, firstly for themanagement and preservation of the data, and secondly, for the capability to analyse the data using sophisticated algorithms and visualisation techniques.

These are the challenges that the laboratory informatics industrynow faces. Increased throughput, cost and error reduction isn’t enoughanymore. The long-term benefit of managing laboratory data andinformation in an integrated way needs to provide not only acquisitionand storage capabilities, but also needs tomake better provision for supporting andadvancing science through extractinginformation and knowledge from the evergrowing data repositories in order to makesense of the data, to uncover correlations andsupport evidence-based decision-making. In addition, informaticssystems need to be sufficiently flexible to be able to adapt to changingbusiness and operational needs. Here lies the paradox; in order tojustify the purchase and deployment of informatics systems, wedepend on the return on investment (ROI) equation to quantifybenefits, i.e. productivity, but the potential long-term benefits mayarise through non-quantifiable factors such as better under standing,better decisions and better science. In other words, the emphasisneeds to be changed from the elimination of waste (time, effort, errors)to providing greater capability, greaterflexibility, and more predictive approaches tosupporting science.

Most laboratories already depend on aninformatics hub comprising any one of, or acombination of the major tools; LaboratoryInformation Management Systems (LIMS),Electronic Laboratory Notebooks (ELN),Scientific Data Management Systems (SDMS)and Laboratory Execution Systems (LES). Thetrend over recent years has been towards the convergence of these tools; in each case the systems originally representeddistinct market sectors, and were populatedby quite separate vendor communities. Thatsituation has changed to the extent that anincreasing number of laboratory data andinformation functions can be accommo -dated within a single vendor solution withthe scope extending from data acquisition todata usage. In the past few years, the mergerand acquisition activity amongst some of themajor players in the laboratory informaticsmarket has seen a specific shift in theirproduct portfolios to the provision of tools tosupport data analysis and visualisation. This

is an important change of emphasis that makes better provision forsupporting science.

The design and infrastructure of the informatics tools will influencetheir ability to adapt to changing business circumstances. Over theyears, ELNs, for example, have evolved in the classic software manner,with increased, extended and more detailed functionality, progressivelyadding to their complexity. But the more simplistic ‘paper on glass’ styleof ELN, as well as cloud-based systems have recently been gainingmarket share with faster deployments and greater user acceptance.Against a background of increased business demand for agility, and aneed to reduce project implementation times, simpler, generic systemsoffer greater opportunity to continually meet changing requirements.Coupled with this shift towards ‘simplicity’ is a decreasing demand fortight customisation and configuration, which significantly add to

implementation times. In some respects thistype of approach, which encompassesmodularity and simplicity, reflects what hasbeen happening with consumer technologies.The combination of mobile devices, task-specific ‘apps’, cloud infrastructures and

sharing/ collaboration through social media has set a precedent for‘user experience’ and raises some interesting questions for thelaboratory informatics industry. If the trend continues to gainmomentum, this may influence greater modularity across the market,opening up the options for best of breed products to meet the specificdemands of different types of laboratory.

With respect to mobile devices, there is a delicate balancing actthat falls somewhere between their desirability and their practical valuein the laboratory. Limited screen sizes, gesture/touch navigation, virtual



With respect to mobile devices, there is a delicate balancing act that

falls somewhere between theirdesirability and their practical value

in the laboratory

© J

ames

Ste

idl /

Shu

tter

stoc

k.co

m

keyboards and their physical vulnerability ina laboratory environment all conspire tochallenge the business case for their use, butfor genuine mobility, coupled with ‘Apps’that offer dedicated functionality and aretailored for the small screen sizes, there is genuine potential. The social mediaargument is an interesting one. Although inthe consumer world, social media serve anentire spectrum of good, bad and ugly usage,the underlying principles are extremelyrelevant to communication, sharing andcollaboration. For this reason, they do havesignificant potential for the laboratory,particularly if they can be incorporated into the controlled environment of theinformatics portfolio. Of course, the ‘cultural’issues remain with respect to user adoption,but using the ‘push’ principles to inform,rather than the traditional ‘pull’, i.e. theinformation is there, but you have to find it, would seem to take a distinctadvantage of the benefits of ‘social media’.

The rate determining steps aroundfurther exploitation of technology in the laboratory are (a) thenecessary constraints associated with scientific and regulatorycompliance and (b) the lack of standards associated with laboratorycomputing. The underlying discipline associated with the scientificmethod generates a risk-averse culture in order to achieve confidencein the data and greater scientific understanding. As a consequence, theprovenance and handling of laboratory data issubject to extensive control in which change ismanaged with considerable caution. Theintroduction of new technologies into thelaboratory therefore moves at a greatly reducedpace compared to the consumer markets. Thelack of laboratory data communication andinterchange standards is well known, and despite some limited, butheroic efforts, there has been little momentum. Everybody understandsthe problem; everybody is aware of benefits that standards could bring,but there has been no collective inertia to move towards a solution. It isnot in the vendors’ business interests to take the initiative, but infairness, nearly all vendors express a willingness to comply with datastandards if there is sufficient market demand. As a user community, wedo not collectively put any pressure on vendors to comply, and so theinitiative falls to collaborative bodies such as Allotrope and Pistoia todrive momentum. Their efforts will be closely followed.

All of this adds up to some interesting times for laboratoryinformatics. With evolving and changing business needs and rapid changes in some consumer technologies that influenceexpectations in the laboratory, the gauntlet has been thrown down. Thecurrent informatics market is migrating towards more modularsolutions, based on a generic core, with optional discipline-specificmodules. Additionally, fit-for-purpose ‘mobile’ applications are beingdeployed to address specific and limited functionality where there is a

sound business case. In general, modularity can create a betteropportunity to enhance the user experience on the assumption thatthe apps, or modules are designed to support specific laboratoryfunctions, can be assembled according to business need, and can worktogether seamlessly. This would still represent a one-size-fits-allapproach, but designed in a way to accommodate the requirements

of multi-disciplinary laboratories, and tostandardise and improve common sub-processes, rather than making compromises.

Ideally, the use of laboratory informaticstools should not be perceived as an intrusivebureaucratic process, but something thatfacilitates the scientific method and doesn’t

intrude on the social and intellectual processes that are essential to thescience. Achieving this objective is essential to joined-up science, andto user acceptance, and is increasingly essential to meet changingbusiness needs. It requires a sympathetic view of the requirements of the different scientific and bureaucratic disciplines and the way in which these functions are managed and provided for, even when organisational demands strive for increased uniformity and consistency.



John Trigg is Founder and Director of phaseFourInformatics, a UK-based consultancy specialising inlaboratory informatics. With extensive experience in thefield of R&D data, information and knowledge manage -ment, John has been author of a number of publications and booklets on Electronic Laboratory Notebooks andLaboratory Informatics, and is the founder of The Integrated

Lab website. He was the recipient of the 2000 International LIMS Award andis currently the Vice-Chairman of the Automation and AnalyticalManagement Group of the Royal Society of Chemistry and an AdvisoryBoard Member of the Institute for Laboratory Automation.

In order to justify the purchase anddeployment of informatics systems, we

depend on the return on investment(ROI) equation to quantify benefits

© a

ngel

lode

co /

Shut

ters

tock

.com

Miss the days of skipping CDs and unwound cassette tapes? Neither do we. Since the introduction of our FDA-licensed

database has made repeat testing so last decade. Prepare for your lab to be rocked yet again by the next chart-topping

innovation in micro QC testing – coming from Charles River 10.20.14.

a passion for innovation. www.criver.com/october20

Why NP characterisation matters in drug deliveryNPs can be fabricated from different materials with different physicaland chemical properties. In addition, they can be surface decoratedwith a range of ligands in order to enhance their therapeutic response(e.g. improving targeting or reducing immune response) or chemicalgroups that improve NPs stability. As a result, a huge number ofcombina tions of NP parameters are possible, with the idea of tailoringthese systems for specific applications. As mentioned above, theinterdependent effect of NP size, shape, composition and surfacechemistry is crucial in dictating their interaction with cells and thereforedrug delivery capability.

Considering NP size, it has been shown that this parameter affectsthe cell uptake efficiency and kinetics. Size-dependent uptake indifferent cell lines has been observed for metal5-7, mesoporous silica8

and polystyrene NPs9, with the maximum efficiency at a NP core size inthe range of 30-50nm10. The effect of size on NP cell uptake and alsotransepithelial transport was also shown for systems displaying ligandstargeting transcytosis systems11. NP size also affects tissue distributionand elimination12, as well as cytotoxicity13.

Surface charge is also an important factor determining the fate ofNP interaction with the biological systems. In terms of cell uptake,positively charged NP penetrate the cell membranes and internalise

The use of materials in nano-scale dimensions is proving to be a promising approach to overcome drug deliverychallenges. ‘Nanomedicine’ technologies are gradually achieving commercial success and reaching the clinic1. Sub-micron nanocarriers have the potential to ferry the therapeutic to its site of action and in this process overcomethe biological barriers2-3 and achieve targeted drug delivery, controlled or stimuli-responsive delivery and protect thetherapeutic from biological milieus. Many different types of nanocarriers have been described, including polymericnanoparticles (NPs), liposomes, solid lipid NPs, micelles, dendrimers and metal NPs among other systems (the terms ‘nanomedicine’, ‘NP’ and ‘nanocarriers’ are used herein to describe all nanosystems). Of particularinterest are nanocarriers with the ability to act selectively and target cell internalisation processes, guiding thetherapeutic into subcellular regions. NP features important in dictating their drug delivery performance, includingtargeted delivery and cellular trafficking, are their size, shape and surface characteristics such as surface charge,chemistry and the distribution of ligands.

PARTICLE SIZING


Particle characterisationin drug delivery

Driton Vllasaliu and Ishwar SinghUniversity of Lincoln

© c

ybra

in /

Shut

ters

tock

.com

with the greatest efficiency compared to neutral and negatively chargedparticles14, probably due to binding to negatively charged groups on thecell surface. However, positively charged particles are also considerablymore toxic compared to negatively charged systems14.

Clearly, the biological response of nanomedicines relies heavily ontheir specific physicochemical characteristics. This is important as forthis class of therapeutics the biological effect generated depends notonly on the action of the active therapeutic(s) incorporated within thesystem but also on the characteristics of other components such asnanocarrier size. In fact, even a small variation in physicochemicalcharacteristics of the system may have a significant impact on theperformance of the nanomedicine. Accurate and detailed characteri -sation of these systems is therefore critical in the development andclinical use of nanomedicines to ensure safe use and reproducibility.

Characterisation of NP sizeThere are several methods available to determine NP size and some ofthese will be discussed further on (for a more comprehensive review onthe topic, the reader is referred to15). Note thateach technique has its strengths and weak -nesses, which have to be considered whencharacterising NPs. The application of aparticular method depends on many factors,including the anticipated NP size range, mono- and polydispersity andNP material. Overall, it is recommended that different NP sizingmethods are employed to ensure robustness, especially whenconsidering the importance on biological response mentioned above.

Dynamic light scattering (DLS) DLS is one of the most commonly used techniques for particle sizemeasurement. This measures the hydrodynamic diameter of a particlevia a laser beam that is scattered by the NPs in a suspension orsolution. The Brownian motion of particles causes random fluctuationsin the intensity of the scattered light around a mean value, used todetermine the particle diffusion coefficient, which is related to itshydrodynamic radius via the Stokes–Einstein relationship15.

DLS is typically used to measure NPs in the 1nm-500nm range,although some systems claim a range of 0.3nm-10μm. While a user-friendly technique, the analysis of multimodal particle size distributionis problematic with DLS16. This is because the results are strongly biasedin the presence of a small fraction of large particles as the signal

intensity of a spherical particle with a radius r is proportional to itsdiameter to the power of 6. To exemplify, when a mixture of 5 and 50nmNPs is measured, the signal of 5nm particles is masked by that of 50nm NPs, with the latter scattering 106 as much light. Consequently,average particle size values determined by DLS are biased. DLStherefore is best suited to measure the size of monodisperse NP samples.

Electron microscopy (EM)EM uses electron beams to visualise NPs. The use of EM is advantageousbecause it provides information on size and shape (morphology) in oneanalysis by direct visualisation. In scanning electron microscopy (SEM)electrons come from the sample surface, whereas in transmissionelectron microscopy (TEM) electrons pass through the sample. TEM has

a superior resolution to SEM and is usuallyemployed to study NP morphology. Due toimage contrast, TEM is most suitable forparticles containing heavier atoms such asgold and silver NPs. TEM, however, is alaborious technique and therefore is notsuited to routine size measurements of largenumbers of NP samples, but is usuallyreserved for morphological characterisation.

Differential Centrifugal Sedimentation (DCS)DCS is based on the principle that withparticles of the same density, larger particlessediment faster than smaller particles.

Although most NPs do not sediment through simple gravitation (due tosmall size), their sedimentation can be induced by centrifugation. Thedisc centrifuge contains a hollow, optically clear disc, which has a

central opening. The disc rotates at a knownspeed ranging from 600-24000RPM. The emptyspinning disc chamber is partly filled withliquid, which forms a liquid ring with a densitygradient. The central opening is used to

inject the sample for analysis. DCS gives a very high resolution anddifferent nanoparticulate species of <5% difference in diameter can beresolved completely. However, analysis times for smaller particles(<50nm) are long.

DCS has recently been used to measure the change in size of goldNPs by changing ligand shells17. For gold–polyamide functionalised NPs,a shift of 0.5nm in the particle diameter was reported followingfunctionalisation and in case of NP functionalisation with a largermolecular weight entity, namely single stranded DNA, this shiftamounted to 2.1nm. This is therefore an example of the high-resolutionNP sizing offered by this technique, which can be used to charact-erise NP, even following functionalisation or surface decoration withspecies with slight variations in molecular weight. The use of DCS tomeasure the size of ligand modified gold NPs was also recently reportedKrpetic et al.18. In this study, ligand shells were composed ofpolyethylene glycol-substituted alkane thiol of different chain length, or oligopeptides. DCS was highly sensitive to small changes in thethickness of particles due to the change in ligand shell, successfully


PARTICLE SIZING

Particle size distributions gold NPs functionalised with a) polyamide (‘Au-PA’) and b) single stranded DNA (‘Au-ssDNA’), compared to the original particle size distribution of gold-citrate (‘Au-Citrate’) NPs. Figure adapted with permission from Krpetić et al.17 Copyright 2012 American Chemical Society

‘Nanomedicine’ technologies are gradually achieving commercial

success and reaching the clinic

measuring variations in the thickness of ligand shells on particlesamounting to as little as 0.1nm.

Nanoparticle Tracking Analysis (NTA)NTA is a technology that enables simultaneous visualisation and multi-parameter analysis of NPs, relating the rate of Brownian motion toparticle size. The particles are visualised based on the light they scatter when illuminated by laser light. Unlike DLS, this technique has the ability to visualise individual part-icles in solution (each scattering source istracked separately), then analyse for size (deter -mined using the Stokes–Einstein equation) andcount/concentration, both under scatter and fluorescence mode. Counting individual particles is useful whendealing with polydisperse samples, although NTA is still unable toseparate fractions of particles with relative size difference of less than50%. Filipe et al. compared NTA with DLS using polystyrene beads19 and

reported that the main advantage of NTA is its unbiased peak resolutionof polydisperse samples, which was not possible to achieve with DLS.

Characterisation of NP surfaceSurface charge: Zeta (ζ) potential The surface charge of NPs is very important in drug delivery because itinfluences the interaction with the biological system, as well as the interaction with other species (including neighbouring NPs) in the

suspension. Measurement of the ζ potentialprovides information on the net charge a NPhas and therefore gives an indication of theelectrostatic charge repulsion or attractionbetween particles in a liquid suspension.

The ζ potential is usually measured by application of an electric field tothe sample and measuring the velocity at which charged species move toward the electrode15. The ζ potential is generally a good measure of the stability of particles in the suspension as

a large repulsion (high ζ potential) betweenparticles means that they will stay away fromeach other (less chance of aggregation),which is generally aimed for nanosystems indrug delivery, and with weaker repulsion thelikelihood of particles coming together(producing aggregates) is higher.

The charge on the surface of particlesand properties of the suspension diluentdetermine the zeta potential. The change inpH and the ionic strength of diluent willaffect particle ζ potential. The ζ potentialmeasurements are therefore highly sensitiveto sample suspension properties and can beused to determine optimum dispersionprotocols and to study the stability ofsamples under changing conditions. It isrecommended that ζ potential measure -ments of NPs are conducted in relevantbiological media/solutions simulating theenvironment within which they interact withthe biological systems.

Surface chemistryThe importance of NP surface chemistry indetermining their biological response isincreasingly being recognised, although thearea remains somewhat poorly understood.A number of different surface-analysistechniques can be useful for NP surfacecharacterisation, including electron spectro -scopies (Auger electron spectroscopy [AES]and X-ray photoelectron spectroscopy [XPS], the latter possibly being the mostwidely used surface spectroscopy), ion-based methods (secondary ion massspectrometry [TOF-SIMS] and low energy ionscattering [LEIS]) and scanning probe

PARTICLE SIZING


Size distribution from NTA and DLS measurements of mixtures of monodisperse polystyrene beads (middle panels) with the corresponding NTA video frame (left panels) and 3D graph (size vs. intensity vs. concentration; right panels). a) 60-nm/100-nm beads at a 4:1 number ratio; b) 100-nm/200-nm beads at a 1:1 number ratio; c) 200-nm/400-nm beads at a 2:1 number ratio; d) 400-nm/1,000-nm beads at a 1:1 number ratio. Taken from Filipe et al.19

The biological response of nanomedicines relies heavily

on their specific physicochemicalcharacteristics

microscopy (atomic force microscopy [AFM] and scanning tunnellingmicroscopy [STM]). For a comprehensive review on the usefulness of these techniques in NP surface chemical analysis the reader isreferred to20.

NP changes within the biological environmentIn a complex biological environment nanocarriers may undergo acomplete transformation in terms of size and surface characteristics.The colloidal stability of NP is influenced by many factors such as theionic strength, pH and composition of thesolution. The formation of a protein corona,which consists of plasma proteins such asalbumin as a major component21-24, maysignificantly alter NP characteristics, includingsize and surface charge (and therefore the likelihood of aggregation).This in turn may completely change the nanocarrier’s biocompatibilityand biodistribution25-26, as well as targeting capacity27. The behaviour ofnanomedicines in the body is therefore an important point to consider

when designing such systems as there is little point in formulatingcomplex nanocarriers, for example with defined size and controlledsurface distribution of targeting moieties/ligands, when such ‘designer’nanocarriers morph into something entirely different in a biologicalenvironment. This point has recently been demonstrated withtransferrin-functionalised NPs, the targeting ability of which disappearsin a biological environment due to a biological media-originatingsurface-adsorbed protein corona27.

With the aforementioned point in mind, characterisation of NPsshould be conducted using appropriatetechniques and for multiple parameters. This characterisation should be performedunder physiologically relevant conditionsreflecting the biological environment of the

body in which the nanosystem is both distributed and exerts its therapeutic action.

ConclusionThe promise of nanomedicine has placed the development of cutting-edge nanosystems at the forefront of drug delivery research.The technology available to analyse NPs has improved considerably,which will no doubt advance our understanding of the influence of NP properties on their biological activity, as well as improve our abilityto translate these systems into the clinic. Unfortunately, the sciencebehind nanotechnology is much more complex than for smallmolecules and not all researchers developing various nanosystems willhave all the tools enabling full characterisation in terms of size, shape,charge and surface chemistry, which is crucial as these propertiesgovern the biological response of nanomaterials.

Furthermore, this characterisation should take place within abiologically relevant environment. There is currently no singletechnique that can provide simultaneous information on all of theseparameters (apart from instrumentation measuring both size and ζ potential), and even for determination of a single parameter such assize, different techniques exist, the use of which has to be carefullyconsidered depending on the NP sample. The availability ofinstrumentation that can provide reliable multiparameter information,combined with ability to accommodate a range of differentnanosystems (e.g. wide NP size range) and easy operation for usersfrom different disciplines is highly desirable.

PARTICLE SIZING


Dr Driton Vllasaliu is a Senior Lecturer at the School ofPharmacy, University of Lincoln. He is a Pharmacist andobtained his PhD in Drug Delivery from the University ofNottingham in 2010. He also works on improved cellmodels of human mucosal tissues as a means to study drug-delivery systems.

Ishwar Singh is a Senior Lecturer in Biological Chemistryat the School of Pharmacy, University of Lincoln. Prior toLincoln, he had held many prestigious fellowships such asthe Alexander von Humboldt fellowship, Germany; andSenior Research Fellowship, CSIR, India. He is an organicchemist. He has developed bioconjugations for DNA, RNAand polymer modifications in water. He is currently leadingresearch in Biologics delivery, Peptides, Sequence selective DNA crosslinking, Nanoparticles modifications for drug delivery applications andbroad spectrum antibiotics.

1. D. Vllasaliu, R. Fowler and S. Stolnik, Expert Opin Drug Deliv, 2014, 11, 139-154.

2. D. Vllasaliu, C. Alexander, M. Garnett, M. Eaton and S. Stolnik, J Control Release, 2012,158, 479-486.

3. R. Fowler, D. Vllasaliu, F. H. Falcone, M. Garnett, B. Smith, H. Horsley, C. Alexanderand S. Stolnik, J Control Release, 2013, 172, 374-381.

4. L. Y. Chou, K. Ming and W. C. Chan, Chem Soc Rev, 2011, 40, 233-245.

5. A. Malugin and H. Ghandehari, J Appl Toxicol, 2010, 30, 212-217.

6. B. D. Chithrani, A. A. Ghazani and W. C. Chan, Nano Lett, 2006, 6, 662-668.

7. J. Huang, L. Bu, J. Xie, K. Chen, Z. Cheng, X. Li and X. Chen, ACS Nano, 2010, 4, 7151-7160.

8. F. Lu, S. H. Wu, Y. Hung and C. Y. Mou, Small, 2009, 5, 1408-1413.

9. J. A. Varela, M. G. Bexiga, C. Aberg, J. C. Simpson and K. A. Dawson, J Nanobiotechnology, 2012, 10, 39.

10. L. Shang, K. Nienhaus and G. U. Nienhaus, J Nanobiotechnology, 2014, 12, 5.

11. R. Fowler, D. Vllasaliu, F. F. Trillo, M. Garnett, C. Alexander, H. Horsley, B. Smith, I. Whitcombe, M. Eaton and S. Stolnik, Small, 2013, 9, 3282-3294.

12. M. Cho, W. S. Cho, M. Choi, S. J. Kim, B. S. Han, S. H. Kim, H. O. Kim, Y. Y. Sheen andJ. Jeong, Toxicol Lett, 2009, 189, 177-183.

13. T. H. Kim, M. Kim, H. S. Park, U. S. Shin, M. S. Gong and H. W. Kim, J Biomed MaterRes A, 2012, 100, 1033-1043.

14. A. Verma and F. Stellacci, Small, 2010, 6, 12-21.

15. K. E. Sapsford, K. M. Tyner, B. J. Dair, J. R. Deschamps and I. L. Medintz, Anal Chem,2011, 83, 4453-4488.

16. X. Y. Lu, D. C. Wu, Z. J. Li and G. Q. Chen, Prog Mol Biol Transl Sci, 2011, 104, 299-323.

17. Ž. Krpetić, I. Singh, W. Su, L. Guerrini, K. Faulds, G. A. Burley and D. Graham, Journalof the American Chemical Society, 2012, 134, 8356-8359.

18. Z. Krpetic, A. M. Davidson, M. Volk, R. Levy, M. Brust and D. L. Cooper, ACS Nano,2013, 7, 8881-8890.

19. V. Filipe, A. Hawe and W. Jiskoot, Pharm Res, 2010, 27, 796-810.

20. D. R. Baer, D. J. Gaspar, P. Nachimuthu, S. D. Techane and D. G. Castner, Anal BioanalChem, 2010, 396, 983-1002.

21. M. S. Ehrenberg, A. E. Friedman, J. N. Finkelstein, G. Oberdorster and J. L. McGrath,Biomaterials, 2009, 30, 603-610.

22. R. Gref, M. Luck, P. Quellec, M. Marchand, E. Dellacherie, S. Harnisch, T. Blunk and R.H. Muller, Colloids and Surfaces B-Biointerfaces, 2000, 18, 301-313.

23. M. Lundqvist, J. Stigler, G. Elia, I. Lynch, T. Cedervall and K. A. Dawson, Proc Natl AcadSci U S A, 2008, 105, 14265-14270.

24. E. Casals, T. Pfaller, A. Duschl, G. J. Oostingh and V. Puntes, Acs Nano, 2010, 4, 3623-3632.

25. J. C. Leroux, F. Dejaeghere, B. Anner, E. Doelker and R. Gurny, Life Sciences, 1995, 57,695-703.

26. S. Stolnik, L. Illum and S. S. Davis, Advanced Drug Delivery Reviews, 1995, 16, 195-214.

27. A. Salvati, A. S. Pitek, M. P. Monopoli, K. Prapainop, F. B. Bombelli, D. R. Hristov, P. M.Kelly, C. Aberg, E. Mahon and K. A. Dawson, Nature Nanotechnology, 2013, 8, 137-143.

References

The use of EM is advantageous because it provides information on size and shape (morphology) in one

analysis by direct visualisation

BackgroundWhile under contract to the United States Navy in the late-1940s,Wallace H. Coulter developed a method for counting and sizingparticles. The method was initially developed to count blood cells, butsoon emerged as a technique that could quickly and accurately countalmost any type of particle. Its acceptance in the field of haematologyis evident by the fact that presently, over 98% of automated blood cellcounters incorporate the Coulter Principle. In the past 60 years, themethod has also been utilised to characterise thousands of differentbiological materials. Bacteria, yeast cells, drugs have all been analysedby the Coulter Principle. The method may be used to measure anyparticulate material that can besuspended in an electrolyte solution.Particles as small as 0.2 micron and aslarge as 1,600 microns in diameter canbe analysed by the Coulter Principle.The method is described in theInternational Standard ISO 13319 and isthe subject of several ASTM standards.

The Coulter PrincipleHow particles are sized and countedThe Coulter Principle is based on thedetection and measurement ofchanges in electrical resistanceproduced by a particle or cell sus -pended in a conductive liquid (diluent)traversing through a small aperture.When particles or cells are suspendedin a conductive liquid, they function asdiscrete insulators. When a dilutesuspension of particles is drawn through a small cylindrical aperture,the passage of each individual cell momentarily modulates theimpedance of the electrical path between two submerged electrodeslocated on each side of the aperture. This change in impedanceproduces a tiny but proportional current flow into an amplifier thatconverts the current fluctuation into a voltage pulse large enough tomeasure accurately. The Coulter Principle states that the amplitude ofthis pulse is directly proportional to the volume of the particle thatproduced it. Scaling these pulse heights in volume units enables a sizedistribution to be acquired and displayed. In addition, if a meteringdevice is used to draw a known volume of the particle suspensionthrough the aperture, a count of the number of pulses will yield theconcentration of particles in the sample.

Simple COULTER COUNTER systems may have only one counter andsize level circuit; while more complex systems, like the Multisizer Series, can obtain particle size distributions automatically in up to 400 size channels. These measurements are made in only a

few seconds, as counting and sizing rates of up to 10,000 particles persecond can be achieved. The accuracy of these size measurements canbe nearly perfect as particles are discretely counted and sized. Colour,refractive index, and opacity of the particles do not affect the results. To count the number of particles in a known volume of a suspension,such as for particulate contamination studies or a blood cell count, thesame volume must be exactly known. A piston displacement meteringsystem is currently used in recent models of the Multisizer and Z-Seriesinstruments to obtain accurate volumes. Please see Figure 1.

The Multisizer 4e is the latest generation of the COULTER COUNTERseries. It uses a Digital Pulse Processor (DPP) for high-speed

digitalisation of the signal, allowing the use of pulse area analysis andother techniques for additional particle characterisation. The data doesnot have to be processed and compressed on the fly, as in earlierversions of the system, but can be stored without loss of information.This enables the raw data to be reprocessed using different settings, aswell as showing sample changes over the length of a run.

Application Note Beckman Coulter


The Coulter Principle

Learn more about the Coulter Principle through our Coulter Principle Short Course at www.particle.com

Figure 1: Coulter Counter Principle

Lean thinkingThe origin of Lean thinking is attributed to the Toyota ProductionSystem (TPS) and was popularised in the western business lore by the

books ‘The machine that changed the world’5 and ‘Lean Thinking’6. The central tenet of Lean thinking is the elimination of waste, wherewaste is defined as anything that increases cost without adding value

Organisations are constantly striving to drive down costs while maintaining the quality of their products and services. In recent years, much has been written in both the academic and practitioner literature on theapplication of Lean principles for the elimination of waste and focusing of energies on value-creating activities. In theory, the adoption of Lean principles by an organisation has the potential to provide the dual pay-off ofincreasing customer satisfaction while reducing cost. The bottom-line benefit of a successful Lean transformationprocess to an organisation is therefore obvious and the reported success stories for true Lean transformations are impressive. Quoted figures such as 90% reductions in inventory coupled with a 50% increase in productivitycapture the attention and imagination of managers1. However, such success stories remain elusive with a success rate of 10% or less being widely reported in the literature1-4. This article explores factors influencing Leantransformation initiatives in organisations.

LEAN MANUFACTURING

Lean, Six Sigma, peopleand organisations

Dr. Stephen McGrath17

Teva Pharmaceuticals Ireland (TPI)


© P

etr V

acla

vek

/ Shu

tter

stoc

k.co

m

for the customer. The five principles underpinning this concept are: 1) value; 2) value stream; 3) flow; 4) pull; and 5) perfection. Lean’s focuson eliminating waste and improving flow has positive effects for productquality as the simplification of processes leads to reduced variation7.Lean is often discussed as a mind-set or philosophy and its emphasison systems thinking, team work and collaborative problem solvingseeks to engage the entire workforce for the development of a cultureof continuous improvement8. The application of Lean principlesfacilitates the implementation of significantprocess improvements without the require -ment for a thorough understanding of theunderlying process. However, this lack of depthof understanding may well contribute toregression to old practices as observed for the majority of Leaninitiatives7. Furthermore, Anthony et al (2003)9 claims that the lack of aclear structure around Lean improvement initiatives constrains thepotential scope and size of the improvement delivered.

People and organisational cultureAccording to Bhasin (2011)10, people-related issues represent the majorobstacles to true Lean transformations, and the author ultimatelyproposes that the realisation of the promise of Lean is dependent on itswidespread adoption across the organisation as a philosophy thatguides all day-to-day business activities10. This people-centric notion ofLean transformations is echoed by many authors including Pepper andSpedding (2010)7, Arnheiter and Maleyeff (2005)8, and Bhasin and Burcher (2006)1.

It is evident that the success of an organisation is determined bythe performance of individuals operating outside of the direct influenceof the organisational leadership. On this basis the major guidingprinciple of a Lean transformation initiative must be the unification ofthe organisation into a holistic integrated business that is focused onachieving clearly defined and measurable objectives that ultimatelydelivers value to the customer. It is therefore clear that organisationsintent on a Lean transformation must develop and apply policies,

systems and rewards that support the visionand goals and foster an organisational climatewhere individuals are engaged and motivatedto continuously improve the processes withwhich they work for the realisation of the

organisation’s vision. Organisations whose cultures are underpinned byLean ideology often employ the concept of Hoshin Kanri for medium- tolong-term strategic planning. This process involves the development ofmulti-layered plans required for achievement of the strategic vision11.This quality planning and management method was developed in Japanin the 1970s and has subsequently been adopted and adapted by someWestern organisations. In this model, senior organisational leadershipdevelop the vision for the organisation and specific stakeholders arethen charged with the development of the specific plans for theachievement of the vision. This process can entail the use of catch-balling where feedback occurs between the stakeholders and seniormanagement and the overall vision may be reshaped depending on thedialogue. It is claimed that this process makes the vision moreachievable, but also engenders a sense of shared ownership and

LEAN MANUFACTURING

People-related issues represent the major obstacles to

true Lean transformations

responsibility due to the employee input process. The plans areultimately linked to the daily work of the employees and consequentlyeverybody knows how their actions feed in to the overall process.Metrics are set to measure performance against the goals and visualmanagement tools are employed to ensure a high level of visibility andaccountability11. Factors with the potential to influence individualengagement with Lean initiatives are outlined in Figure 1.

Lean Six SigmaBisgaard and DeMast (2006)12 have discussed the advent of Six Sigma inthe context of other quality improvement methodologies such as zerodefects, TQM, and quality circles. The authorstrace the lineage of such methodologiesthrough the last 80 years and conclude that SixSigma incorporates many principles fromprevious incarnations of quality managementmethodologies and therefore Six Sigma represents the survival of thefittest ideas. The authors point to the strong project managementstructures of the Six Sigma DMAIC methodology as a significantimprovement over previous quality management approaches such asTQM (see Figure 2, page 45). In addition, the results-oriented approachof Six Sigma, in terms of quantifiable deliverables, is deemed to alsorepresent an advantage over previous approaches. Snee (2010)13 extends

the narrative of Bisgaard and Denhaast (2006)12 when he states that LSSrepresents an evolution of the scientific approach to businessimprovement methodology that incorporates the best of previousmethodologies while providing new tools. The author states that theLean and Six Sigma concepts were first integrated in the late-1990s andthat today LSS is the improvement approach of choice where inclusionof Lean concepts, methods and tools with Six Sigma methodologyprovides a powerful method for the identification of key improve-ment areas and driving rapid process improvement in the identified areas. The synergy of Lean and Six Sigma is discussed in terms ofdevelopment and maintenance of a Lean manufacturing system where

Lean principles are employed to develop the pull systems via which manufacturingprogresses in response to customer demandwhile other Lean tools can add value throughprocess improvement13.

Higgins (2005)14 has stated that implementation of Six Sigma andLean in isolation within an organisation can result in neither being doneeffectively as they are constrained by one another’s needs within theorganisation. Snee (2010)13 states that the comparison of Lean and Six Sigma with respect to what tools from either methodology may beuseful is unhelpful. From a business perspective the focus must be onimprovement and the best tools from both camps must be employed as


LEAN MANUFACTURING

Figure 1: Factors with the potential to influence individual engagement with Lean initiatives

Implementation of Six Sigma and Lean in isolation within an

organisation can result in neither being done effectively

and when they are required. It is therefore apparent that a combinationof both approaches, where Lean tools are used to identify areas withthe highest potential to add value from the customer’s perspective with focussed improvement efforts facilitated through the use of Six Sigma, may represent an appropriate strategy. Typically, Six Sigma isonly used by specific individuals within an organisation for focussing onspecific projects while Lean seeks to engage the wider workforce, butperhaps doesn’t adequately equip individuals with the skills and toolsto do so. The integration of Six Sigma with Lean therefore has thepotential to empower all individuals within the organisation to identify and participate in theelimination of non-value adding activities14.

Hoerl and Snee (2010)15 have proposed atheory for LSS. The authors state that theoptimal team size is four to six people and thatPareto analysis is best utilised to identify the main drivers of a process.The DMAIC problem solving methodology is applicable for all businessprocesses and provides a framework for project deployment. Thereshould be an emphasis on the use of proven scientific tools such asStatistical Process Control (SPC), Design of Experiments (DoE) andMeasurement System Analysis (MSA). The authors stress theimportance of a management structure that facilitates the selection,execution and review of projects and conclude that sustainment of this

structure results in the development of a continuous improvementculture within the organisation.

The key benefit in the melding of Lean and Six Sigma is theintegration of the human and scientific aspects of processimprovement. The scientific statistics-driven approach of Six Sigma andthe people-centric customer-focussed approach of Lean complementeach other to provide a holistic model that provides organisations withthe wherewithal to produce breakthrough results. The emphasis thatSix Sigma places on delivering quantifiable bottom-line results is

conducive to engendering senior managementsupport for initiatives, while the DMAIC processprovides a logical systematic framework forplanning, execution and communication ofproject progress13. In addition, Arnheiter andMaleyeff (2005)8 have described the counter -

balancing influence of both approaches where they claim that excessive Lean can result in processes becoming too rigid torespond to the market, while over-emphasis on reducing processvariation can lead to losing sight on what represents value to thecustomer in the pursuit of zero variation. The authors state that the optimal balance is struck when the approach focusses on thecreation of value from the customer’s perspective with concomitantreduction in process variation. This approach will result in a controlled

cost-effective process that is flexible enough to respond to market requirements8.

Six Sigma deployment in the pharmaceutical industryThe pharmaceutical industry represents one of the mosthighly regulated and therefore restrictive businessenvironments with respect to implementing change. All manufacturing processes must be validated and tightlycontrolled for the purposes of delivering products ofconsistent quality. From a regulatory perspective patientsafety is the preeminent issue and the altering of processes isnot permissible unless it is supported by rigorous scientificevidence that the change doesn’t impact patient safety. The DMAIC methodology is highly amenable to the intro -duction of change in such an environment. The processrequires the clear definition and scoping of the proposedchange, in addition to the assessment of the impact onupstream and downstream processes. Furthermore, theimpact of implemented changes are formally reviewed withfurther actions taken as required. The data and document -ation generated throughout the DMAIC process acts as arecord that can be presented to inspectors as may berequired during regulatory inspections.

Van Arnum (2008)16 has described an organisation-wideLSS deployment by Pfizer. The methodology was used tospearhead a transformation program with the goal ofdeveloping a ‘vision-driven global supply chain network’. Six Sigma methodology was initially used for problem solving and process improvement initiatives within themanufacturing sphere across the organisation and was subsequently expanded to all business processes.

LEAN MANUFACTURING


Figure 2: Project management structures of the Six Sigma DMAIC methodology

The pharmaceutical industry represents one of the most highlyregulated and therefore restrictive

business environments with respect to implementing change

At the time that the article was published Pfizer had over 3,000 GreenBelt and Black Belt projects either completed or in progress with costreductions of 5-20% in addition to inventory and lead-time reductionsof 20-40% attributed to the initiative16. The article also outlines theimplementation of six sigma projects with key vendors to address bothquality and efficiency issues16.

ConclusionThe potential benefit of both engaging and empowering the entireworkforce to actively participate in business improvement initiatives isclear, while the benefit of using structured scientific methods forsupporting and driving these initiatives is as also plain. On this basisLSS may therefore offer a means by which the broad knowledge of thefront line worker can be harnessed to identify improvement projectsand focus the specific expertise required to realise breakthroughimprovements. Furthermore, the structured methodology provides aframework for identification, execution and communication of projectsthat directly impact the bottom line. This approach gains attention andsupport of senior management which is critical for building asustainable continuous improvement culture.

LEAN MANUFACTURING

1. Bhasin, S. and Burcher, P. (2006) ‘Lean viewed as a philosophy’ Journal ofManufacturing Technology Management, Vol. 17, pp. 56-72.

2. Sohal, A. and Eggleston, A. (1994) ‘Lean production: experience amongst Australianorganisations’ International Journal of Operations and Production Management, Vol. 14,pp. 1-17.

3. Baker, P. (2002), ‘Why is Lean so far off?’ Works Management, Vol. 8, pp. 6-15.

4. O’Corrbui, D. and Corboy, M. (1999) ‘The seven deadly sins of strategy’, ManagementAccounting No. 10 pp.1-5.

5. Womack, J.P., Jones, D.T. and Roos, D. (1990), “The Machine that Changed the World”,Rawson Associates, New York, NY.

6. Womack, J.P. and Jones, D.T. (1996), “Lean Thinking”, Simon and Schuster, New York, NY.

7. Pepper, M.P.J. and Spedding, T.A. (2010), “The evolution of Lean six sigma”International Journal of Quality & Reliability Management, Vol. 27, No. 2, pp. 138-155

8. Arnheiter, E.D. and Maleyeff, J. (2005), “The integration of Lean management and sixsigma”, The TQM Magazine, Vol. 17, No. 1, pp. 5-18.

9. Antony, J., Escamilla, J. L., and Caine, P. (2003), “Lean Sigma”. ManufacturingEngineer; Vol. 82, No.4, pp. 40-42.

10. Bhasin, S. (2011) ‘Performance of organisations treating Lean as an ideology’ BusinessProcess Management Journal, Vol. 17, pp. 986-1011.

11. Jolayemi, 2008

12. Bisgaard, S., DeMast, J. (2006), “After Six Sigma-What’s next?”, Quality Progress, Vol.39, No. 1, pp. 30-36.

13. Snee, R.D. (2010), “Lean six sigma – getting better all the time” International Journal ofLean six sigma Vol. 1 No. 1, 2010 pp. 9-29.

14. Higgins, K.T. (2005), “Lean builds steam”, Food Engineering: The Magazine forOperations and Manufacturing Management, available at: http://www.foodengineeringmag.com/Articles/Feature_Article/1e1b90115c2f8010VgnVCM100000f932a8c0____.

15. Hoerl, R.W. and Snee, R.D. (2010), “Statistical thinking and methods in qualityimprovement: a look to the future”, Quality Engineering, Vol. 22, No. 2.

16. Van Arnum, P. (2008), “Manufacturing Insights: Pfizer”, Pharmaceutical Technology July 32, 7, p 50.

17. The views expressed herein are the views of the presenter only and not those of anycompany, employer, or organisation associated with the presenter.

References

Dr. Stephen McGrath is the Site Microbiologist at TevaPharmaceuticals Ireland (TPI). He is currently Studying fora MBS in Lean Practice and is leading a Lean laboratorytransformation at the TPI site. He received his PhD inMolecular Microbiology from University College Cork in 2001 and spent six years in academic research andteaching before moving to industry.

This autumn, the scientific elite in pharma -ceutical research will again come together atMipTec, as they have done annually for over 12 years. The event has grown from its originsas a specialist conference for laboratoryautomation into a leading global conferencein the life sciences sector. By offering a broadand diverse, but also deeply scientific,conference programme, MipTec plays a vitalrole in helping pharma and biotech scientistssuccessfully attack the significant challengesin modern-day drug research and develop -ment work.

The exchange of the latest scientificfindings and technological innovations, as well as the improving integration of science and technology will be at the centre of this three-day conference. For theorganisers, it is especially important to createan interactive platform for researchersworking in the life sciences, who wouldotherwise rarely meet.

The programmeThe 2014 conference theme is ‘TranslatingScience into Drugs’, covered by internationallyrenowned keynote speakers in the drugdiscovery and life sciences field. MipTec’s 11 Science Forums cover cutting-edge develop -ments that enhance drug discovery: Aging,Drug Discovery Information Management,GPCR, Infectious Diseases, MedicinalChemistry, Next Generation Sequencing,Peptide Therapeutics, Protein Production, as

well as Stem Cells in Biomedicine, Trans -lational Medicine and Synergy Forum.

The conference provides a platform for net working and scientific exchange foracademic and industrial scientists. With morethan 100 exhibitors presenting state-of-the-artequipment and services to advance biomedicalresearch, more than 100 scientific presenta -tions and more than 100 poster exhibitors,delegates will get expert insights into mostrecent developments and experiences in alldimensions of drug discovery. Delegates willalso have the opportunity to discuss strategicand business oriented issues and learn morecareer options in many of the exceptionalsatellite focused sessions.

Keynote presentationsMipTec 2014 is proud to welcome the followingthree keynote speakers at the conference:� Tuesday 23 September 2014: Dr. Jörg

Reinhardt, Chairman of the Board ofDirectors, Novartis AG

� Wednesday 24 September 2014: Prof.Patrick Aebischer, President, EcolePolytechnique Fédérale de Lausanne(EPFL)

� Thursday 25 September 2014: Dr. LorenzMayr, Vice President, Reagents & AssayDevelopment, AstraZeneca Ltd.

Networking eventsWelcome ReceptionThis year’s conference will offer a ‘Welcome

Reception’ on Tuesday 23 September 2014 forexhibitors and delegates in Hall 4.1 in theCongress Center Basel. All attendees will havethe opportunity to network with colleaguesand opinion leaders in a relaxed atmosphere.

Poster Session & Apéro The MipTec Poster Session will be held onWednesday 24 September 2014. The authors ofthe scientific posters will be available forquestions. Posters, which got recognisedthrough their scientific quality, will benominated for poster prizes, sponsored by SLAS.

Industrial ExhibitionParallel to the scientific programme, theMipTec exhibition will take place in Hall 4.1 in the Congress Center Basel. Parallel to the MipTec Drug Discovery Conference, on a 900m2 area, exhibitors will showcase their newest developments, products and services in the field of laboratory andresearch reagents, laboratory automationand instruments as well as hard- and soft-ware for the computer-supported analysis and medicinal chemistry of industry leaders anddecision-makers in the life sciences area.

The largest European conference on drug discovery, MipTec, continues to grow and offers a high-calibre programmefrom 23-25 September 2014. Over 3,000 scientists from industry and academia are expected to attend thepresentations and scientific forums at MipTec.

SHOW PREVIEW: MIPTEC 2014

Gathering leading figures from drugdiscovery and life sciences in Basel


Date: 23-25 September 2014Location: Basel, SwitzerlandFor more information on MipTec 2014,please visit www.miptec.com

Eckn

auer

+Sc

ho

ch A

SW

NIR

S.A

1.10

05-E

PR ©

201

3 M

etro

hm U

SA, I

nc.

The solution is «NIR»!

Metrohm NIRSystems, to be exact. Precision near-infrared technology & expert applications support cover your entire spectrum of pharmaceutical testing – from raw materials inspection to in-process monitoring to final product quality control.

• Proven technology & expertise 50 years & 50 patents give you

confidence in our systems – and your results

• Best signal-to-noise ratio For precise and reproducible spectra

• Easy to operate User-friendly software with cascading

libraries simplifies material identification

www.metrohm-nirs.com

Tasked to work faster & more efficiently?


SPONSORS

51 Moving towardscontinuous manufacturingwith NIRS and NIR-CI systems José Manuel Amigo, Department of Food Science, University of Copenhagen, Milad RouhiKhorasani and Jukka Rantanen, Department ofPharmacy, University of Copenhagen, and PoulBertelsen, Tekada Pharma A/S

57 Monitoring ofpharmaceutical powdermixing by NIRspectroscopy Lizbeth Martinez, Novartis Switzerland

NIR

© H

irurg

/ Sh

utte

rsto

ck.c

om

How to implement NIR spectroscopyinto the pharmaceutical processesNear Infrared spectroscopy as a great PAT tool for pharmaceuticalprocesses – from rawmaterial ID, integratedprocess control and to finalproduct testing


WebinarDate: Tuesday 7 October 2014Time: 15:00 BST (UK) / 16:00 CET (Europe) / 10:00 EDT (USA)Duration: 60 minutes

FREE-TO-ATTEND

This webinar will focus on benefits of using NIR spectroscopy in severalpharmaceutical processes. Examples of NIR application for raw materialID, process control testing and final product will be given.

Challenges in implementing NIR spectroscopy in the analytical processwill also be discussed.

Confirm your attendance at: www.europeanpharmaceuticalreview.com/nir-webinar

Speakers:

Dr. Ke Hong Senior Project Manager,

Pfizer Global Supply

Denise Root NIR Marketing Manager,

Metrohm USA Inc.Organised by: Supported by:

WEBINAR PREVIEW

Conventional pharamaceutical manufacturing of solid dosageThe first stage in solid drug manufacturing is synthesising of the active pharmaceutical ingredient (API) in a chemical manufacturingplant. Afterwards, the API is normally transferred to another place-ment, where it is produced in batches of solid dosages (e.g. tablets).The development process of tablets can be divided into the followingthree steps:1. The drug is formulated in lab-scale2. Production of pilot and clinical batches3. Up-scaling from lab-scale to production scale.

Optimisation and validation is necessary at each scale level, since thesettings according to process and formulation are not transferable fromlab-scale to production-scale. Furthermore, the last step is costly andtime-consuming and prevents a fast market launch1,2. An example ofconventional tablet manufacturing process in production-scale isdepicted in Figure 1 (page 52). After each unit operation is completed asample of the intermediate product is collected and tested at off-linelaboratories according to critical quality attributes for the intermediateproduct. If the intermediate product complies with applicable analyticalrequirements it is transferred to subsequent unit operation for futureprocessing. The same procedure applies to the last unit operation in

In the past, the pharmaceutical industries have been applying batch processing during manufacturing of pharmaceutical products because it serves well to the industry and the regulatory agencies. Conventionalpharmaceutical manufacturing is generally accomplished using batch processing together with time-consuming off-line laboratory measurements, conducted on many randomly collected samples to evaluate quality attributes.The principle of batch processing is profound quality control of the intermediate-product and the final product after each unit operation.

IN-DEPTH FOCUS: NIR


© N

olte

Lou

rens

/ Sh

utte

rsto

ck.c

om

Moving towards continuousmanufacturing with NIRSand NIR-CI systems

José Manuel AmigoDepartment of Food Science,University of Copenhagen

Milad Rouhi Khorasani and Jukka RantanenDepartment of Pharmacy,University of Copenhagen

Poul BertelsenTekada Pharma A/S

process. If the final product complies with applicable analyticalrequirements it is packed and ready for the market .

Continuous manufacturing, process analyticaltechnologies and Quality by Design paradigmThe pharmaceutical industry is required by the regulatory agencies toconstantly assess and assure the drug quality and safety at any time.The uncertainty of approval by the regulatory agencies is one of theimportant reasons why the pharmaceutical industries have not beenmotivated to take initiative to move from batch production tocontinuous production. However, in recent years, continuousprocessing has gained importance in the pharmaceutical industry.Moreover, the regulatory bodies have shown an enormous interest inmoving toward continuous processing in order to improve quality in pharmaceutical production. The U.S. Food and Drug Administration

(the FDA) has outlined a regulatory framework through which they tryto encourage the pharmaceutical industry to implement state-of-the-art scientific initiatives to improve and optimise pharmaceuticaldevelopment, good manufacturing practice, and quality assurance ,the Quality by Design (QbD) paradigm.

One of the main approaches from the regulatory framework forimproving pharmaceutical manufacturing is the application of ProcessAnalytical Technologies (PAT). PAT involves real-time quality evaluationand control of the manufacturing process, which may be a help for thepharmaceutical industries to better understand the proposed productand process design. PAT can also improve theability to identify and understand the CriticalProcess Parameters (CPP) of the equipmentwhich affects the Critical Quality Attributes(CQA) of the product. By controlling the CPPswithin well-defined boundaries, PAT allowsthe manufacturer to produce a product withconsistent quality and waste reduction.Therefore, the implementation of PAT in real-time industrial production set-ups is crucialbefore continuous manufacturing canbecome a reality in the pharmaceuticalindustry. In order to implement PAT, thefollowing three main PAT tools have to be complied:

� Use of multivariate data analysis (MVDA) and design of experiments(DoE) to determine the CPPs

� Use of fast, non-destructive and reliable analytical tools such asnear-infrared spectroscopy (NIRS) with fiber optics or near-infraredchemical imaging (NIR-CI) for real-time analytical measurements of the CQAs

� Use of Statistical Process Control (SPC) software, which collect and process data with time for specific processes with the aim of quality control.

During a continuous process it is important to measure and ensure renewable uniformity during the process run. By using non-invasive spectroscopy NIR-spectroscopy or NIR-CI in combination with multivariate data analysis in QbD context, it is possible to obtain real-time concise process information that can lead to the

creation of improved control strategies and better process understanding forcontinuous manufacturing of solid dosagepharmaceuticals. A flowchart of continuousmanufacturing is illustrated in Figure 2 .

Near-infrared spectroscopy andmultivariate data analysisImplementing PAT in the pharmaceuticalindustry requires the development of newanalytical methodologies that can be readilyadapted to existing industrial processes. Inthis sense, the binomial association of near-infrared spectroscopy (NIRS) and multi -variate data analysis (MVDA) has been

demonstrated to be an extremely powerful tool for real-time controlling and monitoring pharmaceutical processes. NIR and MVDA spectroscopy is applied to qualify and/or quantify for example,the active pharmaceutical ingredients (APIs) and excipients, tocharacterise particle size, powder blending, drying and coating of an in-process product . Such proven success has gained wide accept-ance by pharmaceutical manufacturers and regulatory agencies. A simple example of how NIRS and MVDA can be implemented under PAT framework is described with an example shown in Figure 3a-3d (page 53) . The aim of this case study was the


IN-DEPTH FOCUS: NIR

Several unit operations are included in the conventional tablet manufacturing. Blending is the first unitoperation and coating is the last unit operation. After each unit operation is completed, a sample of the product iscollected and tested at off-line laboratories according to critical quality attributes for the product. The stop signsindicate off-line laboratory testing such as high performance liquid chromatography or gas chromatography-massspectrometry, etc.

A flowchart of continuous tablet manufacturing. During manufacturing the process is monitored by process analytical tools in real-time. It is possible to develop feedback controls for accepting or rejecting the productintermediate based on acceptation limits. It is also possible to adjust the process parameter during manufacturing.The yellow monitoring arrow signs indicate real-time process.

development of a methodology for theestimation of the average granule size of aroller compaction process. Fine powders areforced and compressed between twocounter rotating rolls into ribbons. Subse -quently, ribbons are granulated throughscreens to achieve a desired granule size (seeFigure 3a). In this step, it is crucial to have aprecise knowledge about the median granulesize since a high fraction of fines (granulessize <125 μm) can cause segregation issuesduring tableting.

NIR spectra capture chemical andphysical variability in the samples, which can be used in several applications. In this study the physical variability is the mostinteresting. As demonstrated in Figure 3b,the NIR spectra of various granule sizes lead to baseline shift (i.e. Light scattering)towards higher apparent absorbance11. The smallest granule size corresponds to thelowest spectrum in the figure. Each spectrumcorresponds to a different size sieve fractionwherein the median granule size (d0.5) variesbetween 50 and 900 μm. A multivariatecalibration model (partial least squares – PLS– in this case) can then be developed toestablish a linear correlation between the

IN-DEPTH FOCUS: NIR

Figure 3: (a) The basic concept of roller compaction is to compress fine powders between two counter rotating rollsinto ribbons. Ribbons are chopped and granulated through screens to achieve desired granule size. The mean granulesize is estimated during process by using NIRS and MVDA. (b) Upon increasing granule size increased absorbanceis observed. (c) PLS regression fit correlating measured median granule size (laser diffraction method) to predict themedian granule size (NIR). (d) The dots indicate the process status within the acceptance limits; green = process isstable and red = process is not stable.

NIR spectral information (X variables) and the median granule size (Y response), see Figure 3c (page 00). This model, after validating it with normal operating condition (NOC) batches andestablishing normal condition boundaries can, indeed, be used for real-time estimation of the median granule size during furtherprocesses. In order to ensure that the process is stable and the PLS-model is working properly SPC-tools such as control-charts can be created. Figure 3d (page 53) illustrates a control chart showing the estimated median granule size for a series of time-pointsduring the process time, helping to determine whether the process is under controlled conditions. The green central line shown in Figure 3d (page 53) indicates the average value of the granule size. The blue control limits indicates Upper Classification Limit (UCL) and Lower Classification Limit respectively (LCL). At the time-point one to five the process is stable, which is indicated by dots having green colour. An unintended change in optimal CPP for example,change in compression force will influence the CQA in this case thegranule size. Lower compression force leads to decrease in granule size.At time-point seven-and-eight the process is not stable which isindicated by the dots having red colour. After adjusting the compressionforce to optimal setting the process goes towards a stable phase, time-point 10 to 13.

By applying control charts it is possible to monitor and adjust thequality control of final products during manufacturing process. The aforementioned case study is an example of one of many NIR andMDVA approaches that are available for real-time process monitoring,adjusting and knowledge acquisition.

Near-chemical imaging and multivariate data analysisNear-chemical Imaging (NIR-CI) integrates imaging and spectro-scopy to obtain both spatial and spectral information from anobject. With respect to other applications related to surfacecharacterisation for example, distribution of components and porosity distribution for specific matter, conventional NIRS is limited because it is a single point spectroscopy technique. Thislimitation can be overcome by applying NIR-CI as this technique adds anew dimension to conventional NIR spectroscopy. NIR-CI is able toobtain high quality images of spatial distribution of differentconstituents for a specific matter. According to the literature (9) NIR-CI,together with MVDA, has demonstrated its usefulness in variousapplications such as determination of content uniformity, particle size and distribution of all components in tablets, moister content and location etc.10,12,13.

Tableting is, arguably, one of the most important unit operations in pharmaceutical manufacturing. The com pression pressure during tableting is a crucial CPP for tablet dissolution profile and drug release. To follow we show a simple case study: NIR-CI joined with Principal Component Analysis (PCA) has been applied forinvestigation of the possibility of distinguishing between pharma -ceutical tablets compressed at various pressures and visualisation of the Active Pharmaceutical Ingredient (API) distribution within the tablets.

Eighteen tablets with identical compo sition were compressed intriplicate at various compression forces; 1, 2, 4, 6, 12 and 16 kN. Figure 4adepicts the score image of the first principal component of the PCA

model, which illustrates the separation ofthe different tablets on the basis of theircompression pressure. The dark blue colourrepresents the tablets compressed at lower pressure where the dark red colourrepresents tablet compressed at higherpressure. The NIR spectra are influenced bythe tablet compaction force. Increasing thecompaction force leads to a baseline shift towards higher absorbance. The firstprincipal component explained most (93.1%)of the variation and the evaluation of loadingindicated that this was related to a baselineshift depicted in Figure 4b.

The score image includes secondaryinformation which may be related to the API surface distribution in the tablets. The dark red colour represents a highcontent of API where the dark bluerepresents low content of API as shown inFigure 4c. The second first principalcomponent explained (6.85%) of thevariation which causes the API variation sincethe pattern of the loading resembles thespectrum of the pure API (see Figure 4d).

This aforementioned approach isallowing direct qualitative comparison withcontrol products. A prediction model could


IN-DEPTH FOCUS: NIR

Figure 4: (a) Score image of tablets compressed at different pressures. Blue indicates low pressure and red indicateshigh pressure. (b) The NIR spectra are influenced by the tablet compaction force. Increase compaction force, lead tobaseline shift towards higher absorbance. The loading is related to baseline shift. (c) Score image of API distributionwithin each tablet compressed at different pressures. Red indicates high API content and blue indicates low APIcontent. (d) The loading is related to API variation.

also be developed, if a real-time prediction of compression force duringprocessing is desired.

ConclusionFor many decades, pharmaceutical industries have exclusivelycompeted in the field of innovation of new pharmaceutical products. In this context the pharmaceutical industries expand anotified amount of capital on Research and Development (R&D). It isevident that the Pharmaceutical industries need more capital in thefuture for R&D, based on increases in competition, further increases inproportion of generic utilisation, opening of new markets, and thepressures for price controls. Therefore the pharmaceutical industrieshave to choose other strategies such as implementation of PAT, toreduce expenses.

One field that is obvious for beginning to apply new strategies is the field of manufacturing. The regulatory bodies encourage thepharmaceutical industry to move towards continuous manufacturing.Implementation of PAT includes a system for designing, analysing andcontrolling manufacturing during processing of CQAs and therebyensuring high quality of the final product.

One of the most prominent and used process analytical techniqueswhich already is used by a number of pharmaceutical industries is NIRS.Recent years of technological advances within the field have helped to

transfer the technique from laboratory testing to real-time processmonitoring during production.

An upcoming technique that has gained more interest from theindustries is the NIR-CI. The basis of the technique is relatively new.Several industries are using NIR-CI for laboratory testing, but only few industries are trying the capabilities of NIR-CI in production line.Before the technique can become a reality in the production line, hardware and software improvements are needed.

In the future there will be an increasing need to reducemanufacturing, quality costs and to improve product quality will drawthe pharmaceutical industries towards implementation of PAT andaiming for continuous manufacturing.

AcknowledgmentsThe data presented in this article were obtained by Milad Khorasaniduring his PhD project under supervision of José M. Amigo, PoulBertelsen and Jukka Rantanen.

IN-DEPTH FOCUS: NIR


José Manuel Amigo obtained his Ph.D. (Cum Laude) inChemistry from the Autonomous University of Barcelona,Spain. Since 2007 he has been employed at the Departmentof Food Science, Spectroscopy and Chemometrics Group ofthe University of Copenhagen, Denmark as AssociatedProfessor. Current research interests include hyperspectralanalysis, pharmaceutical research, chemometrics,

environmental modelling, process analytical technologies, curve resolutionand MATLAB programming. He has authored more than 70 publications(50+ peer-reviewed papers, books, book chapters, proceedings, etc.) andgiven more than 40 conferences in international meetings. José hassupervised or is currently supervising seven masters, post docs and Ph.D.students and he is an Editorial Board Member of four scientific journalswithin chemometrics, pharmaceutical sciences and analytical chemistry.Moreover, he has recently received the 2014 Chemometrics and IntelligentLaboratory Systems Award. Email: [email protected].

Milad Rouhi Khorasani is currently doing his PhD projectat the Department of Pharmacy of the University ofCopenhagen. As part of his PhD project, he is developingnew control strategies and creating a fundamentalunderstanding of the impact of Critical Quality Attributes(CQAs) in the current unit operations and also the overallimpacts of CQAs in connected unit operations on the finalsolid dosage form. He is mainly focused on three unit operations: powderblending, dry granulation (Roller compaction) and tablet compression.

Jukka Rantanen is Professor of PharmaceuticalTechnology and Engineering at the Department ofPharmacy at the University of Copenhagen. He received hisPh.D. from the University of Helsinki in 2001, completedpostdoctoral visit at the Department of Industrial andPhysical Pharmacy (Purdue University, USA) in 2003, and joined the faculty at the University of Copenhagen in

2006 as a Full Professor. His research is focusing on development of futuremanufacturing solutions for medicinal products and especially, molecular-level process analysis of solid dosage forms using spectroscopic techniquescombined with multivariate data analysis tools. Jukka has supervised or iscurrently supervising 25 post docs and Ph.D. students and he is an Editorial Board Member of four leading scientific journals withinpharmaceutical sciences and chemical engineering. He has co-authoredmore than 160 scientific papers and holds three patents/patent applications.

Poul Bertelsen has a M.S. Master of Science (pharm) fromthe Royal Danish School of Pharmacy and presented aPh.D. Thesis titled ‘Filmcoating by fluidized bedtechnology’ in 1987 at the Royal Danish School ofPharmacy. Poul’s main area of interest is optimisation,monitoring and description of pharmaceutical manu -facturing processes, plus the development process as suchincluding the use of QTPP, DoE and QRM.

1. Betz G, Junker-Burgin P, Leuenberger H. Batch and continuous processing in theproduction of pharmaceutical granules. Pharmaceutical development and technology.2003 Aug;8(3):289-97. PubMed PMID: 12901694. Epub 2003/08/07. eng.

2. Mascia S, Heider PL, Zhang H, Lakerveld R, Benyahia B, Barton PI, et al. End-to-endcontinuous manufacturing of pharmaceuticals: integrated synthesis, purification, and finaldosage formation. Angewandte Chemie (International ed in English). 2013 Nov18;52(47):12359-63. PubMed PMID: 24115355. Epub 2013/10/12. eng.

3. Bequette BW, Conway BR. From Pilot Plant to Manufacturing: Effect of Scale-up onOperation of Jacketed Reactors Solid Dosage Forms.

4. Pharmaceutical cGMPs for the 21st century – A risk based approach

5. A F. PHARMACEUTICAL CGMPS FOR THE 21ST CENTURY —A RISK-BASEDAPPROACH 2004. Available from: http://www.fda.gov/downloads/Drugs/DevelopmentApprovalProcess/Manufacturing/QuestionsandAnswersonCurrentGoodManufacturingPracticescGMPforDrugs/UCM176374.pdf.

6. FDA A. Guidance for Industry – PAT – A Framework for Innovative PharmaceuticalDevelopment, Manufacturing, and Quality Assurance. 2004. Available from:http://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/ucm070305.pdf.

7. FDA A. Guidance for Industry – Process Validation: General Principles and Practices2011. Available from: http://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/UCM070336.pdf

8. International Conference on Harmonisation of Technical Requirements for Registrationof Pharmaceuticals for Human Use. Pharmaceutical Development Q8 2009. Availablefrom: http://www.ich.org/fileadmin/Public_Web_Site/ICH_Products/Guidelines/Quality/Q8_R1/Step4/Q8_R2_Guideline.pdf.

9. Roggo Y, Chalus P, Maurer L, Lema-Martinez C, Edmond A, Jent N. A review of nearinfrared spectroscopy and chemometrics in pharmaceutical technologies. Journal ofpharmaceutical and biomedical analysis. 2007 Jul 27;44(3):683-700. PubMed PMID:17482417. Epub 2007/05/08. eng.

10. Reich G. Near-infrared spectroscopy and imaging: basic principles and pharmaceuticalapplications. Advanced drug delivery reviews. 2005 Jun 15;57(8):1109-43. PubMedPMID: 15899537. Epub 2005/05/19. eng.

11. Short SM, Cogdill RP, Wildfong PL, Drennen JK, 3rd, Anderson CA. A near-infraredspectroscopic investigation of relative density and crushing strength in four-componentcompacts. Journal of pharmaceutical sciences. 2009 Mar;98(3):1095-109. PubMedPMID: 18623193.

12. Amigo JM, Ravn C. Direct quantification and distribution assessment of major and minorcomponents in pharmaceutical tablets by NIR-chemical imaging. European journal ofpharmaceutical sciences : official journal of the European Federation for PharmaceuticalSciences. 2009 May 12;37(2):76-82. PubMed PMID: 19429413. Epub 2009/05/12. eng.

13. Sasic S. An in-depth analysis of Raman and near-infrared chemical images of commonpharmaceutical tablets. Applied spectroscopy. 2007 Mar;61(3):239-50. PubMed PMID:17389063. Epub 2007/03/29. eng.

References

WebinarDate: Thursday 25 September 2014Time: 15:00 BST (UK) / 16:00 CET (Europe) / 10:00 EDT (USA)Duration: 60 minutes

FREE-TO-ATTEND

Optimising target-based assays and streamlining hit-to-lead processes are key for aproductive R&D drug pipeline. Researchers in both the pharmaceutical and biotechindustries, as well as in academic environments, are increasingly searching for noveltechnologies and related services that enable them to both innovate and speed-up theirresearch pipeline.

The creation of disease models for target validation and reporter cell lines for high-content screening assays are good examples of where one needs high-technologyknowledge and cell engineering expertise to be able to efficiently create the ideal cellmodel in a reasonable time frame. Trying to have a grip on novel gene editing knowledgeand hands-on experience is a time and cost consuming effort. For this reason, researchersare increasingly deciding to externalise that part of their work, in order to focus on target-specific research and other aspects of drug development.

In this free-to-view webinar we will discuss how the decision was taken on a knock-outapproach to generate iPSC disease models to more efficiently and quickly validate twopotential lung cancer targets. We will also present considerations for undertakingsuccessful cell engineering projects for high-content screening assay development andtarget validation.


Confirm your attendance at: www.europeanpharmaceuticalreview.com/gene-editing-webinar

Speakers:

Ronald Van Brempt Principal Investigator,

LUMC

Mark Gerber Supervisor/Principal R&D

Scientist, Cell Design Studio™,Sigma-Aldrich

Organised by: Supported by:

Gene editing partnerships to enhance drug pipeline productivity

Outsourcing target-specific disease model & reporter cell line

engineering to enhance target validationand optimise hit-to-lead processes

WEBINAR PREVIEW

Pharmaceutical manufacturing is moving toward real-time release ofpharmaceutical products. This goal can only be achieved by clearlyunderstanding the manufacturing process and by implementing the suitable technology for manufacturing and for process control. Each unit operation brings challenges that need to be assessed in orderto prevent compromising the quality of the final product. Solids mixingis a key unit operation by which two or more components (activeingredients and excipients) are randomised. Blending performance islargely dependent on the physical characteristics of the materials andthe process conditions. This is exemplified by a fishbone diagram inFigure 1 on page 58. It is clear that the assessment of a good blendquality requires a good understanding of the variables that can have astrong impact on the powder blend. As defined in the Quality by Design(QbD) initiative by the ICH1, the quality of the final product cannot betested in the product, but rather should be built-in by design through

the development process by the identification of the critical qualityattributes in order to establish the right control strategy. Processmonitoring is an additional tool to guarantee a high and predefinedquality standard and furthermore offers the possibility to react at anystage of the process if any parameters drift from the normal operatingrange. The FDA’s Process Analytical Technology (PAT) initiative2

also promotes the process understanding by encouraging thepharmaceutical industry on the implementation of new technologiesand by predesigning the quality of the final product. One of the mostwidespread PAT tools is near-infrared (NIR) spectroscopy, which is a fastand non-invasive analytical technique that is suitable for the real-timemonitoring of a blending process. Another characteristic of NIRspectroscopy is that the sample does not require previous treatmentand can be measured as it is. Given that, this vibrational technique issensitive to physical and chemical attributes, the resulting spectra need

Powder mixing is a central and extremely important unit operation that is practiced to a great extent wheneverparticulate material is processed. In the pharmaceutical industry, blending is involved in the manufacture of soliddosage forms, which include tablets, capsules, and granules. Therefore, powder blending cannot be overlooked anda correct control strategy is fundamental. One of the technologies that has attracted a lot of attention from thepharmaceutical industries as well as the health authorities is near-infrared (NIR) spectroscopy. NIR spectroscopycan measure bulk samples without any preceding treatment, thus making it a very appealing technology for the real-time monitoring of pharmaceutical processes.

IN-DEPTH FOCUS: NIR


© M

aria

Maa

rbes

/ Sh

utte

rsto

ck.c

om

Monitoring ofpharmaceutical powder mixing by NIR spectroscopy

Lizbeth MartinezNovartis Switzerland

to be properly analysed in order to focus the study to the qualityattribute of interest.

NIR spectroscopy holds great potential for monitoring pharma -ceutical manufacturing processes in-line and for end-product analytics.However, the pharmaceutical industry is tightly regulated and thereforethe implementation of NIR spectroscopy needs careful risk assessmentdue to the fact that predictions are obtained by statistical correlationsbased on established assays rather than being a direct assay. Thus the

establishment of comprehensive methodologies is needed for NIRspectroscopy quantification, which is specific for powders and soliddosage forms, with the aim of minimising effects originating from thephysical properties.

Blend homogeneity determinationConventional blend uniformity analysis is time consuming, labourintensive, prone to induced segregation during sampling, andhomogeneity determination is focused on the active pharmaceuticalingredient (API) level in a static way. Application of NIR spectroscopy as an on-line monitoring tool can avoid the drawbacks of the convent -ional method.

A full understanding of the physical state of the APIs in theformulations is of significant importance because: on the one hand,stability and dissolution behaviour can be affected and, on the otherhand, robust calibration models must be developed since NIR spectracontain both chemical and physical information. Therefore, pre-processing techniques and wavelength selection ranges should becarefully chosen to extract the chemical information that is mainlycorrelated with the API concentration.

Assessment of homogeneity by NIR spectroscopy however is a

common chall enge for blend uniformity determination and differentprocedures are described in literature such as: principal componentanalysis and dissimilarity with the final blend spectrum , principalcomponent scores distance analysis , determination of homo geneity bythe bootstrap algorithm and chi-square analysis ; by the mean squareof differences between spectra for blend uniformity monitoring, thismethod does not require a reference spectrum ; Caterpillar algorithmevaluates spectral changes by moving windows followed by an F test for

the comparison of the signal variations .Moving block of standard deviation (MBSD)determines the end-point of the blendingprocess qualitatively by the MBSD methodthat consists of selecting a set of consecutivespectra (block or window size) then thestandard deviation for the absorbance at the selected wavelength range is calculated,followed by the mean standard deviationcomputation of that set. Mean standarddeviation is plotted against time, subse -quently the spectral set is shifted by onetime unit and the calculations are repeated .

Calibration approachesOne of the challenges of measuring ablending process is that the powders areunder continuous movement, thus thedifferent moving dynamics (differentphysical presentation of the sample) caninterfere with the acquisition of reliableresults. Andersson et al. , examined mov-ing solids with a NIR Fourier transformspectrometer, pointing out that powderspeed influenced the quality of the resultingspectra, later studies have showed the

feasibility of measuring flowing powders. Besides the dynamic nature ofthe measurement, the inhomogeneities due to the performance of theblender as well as the powder properties are critical.

A second challenge of the NIR blend uniformity monitoring is the acquisition of calibration samples for the construction of thequantification model.

Off-line calibration is one approach in which a bigger amount ofblends can be measured and the API concentration is well-known.Another approach consists of stopping the blender at different timepoints to scan the powder bed by NIR and to take samples for off-lineanalysis. There are several methods for the spectral acquisitions whichdiffer on the scale of mixing, the dynamic or static measurement, on-line or off-line, gravimetric or chromatographic reference methods,etc. Karande et al. exemplified the complexity in acquiringrepresentative calibration samples. They acquired the samples in staticand dynamic modes, showing that the better predictions were obtainedwhen the dynamic samples were employed. Several studies have beenperformed in order to establish the best calibration procedure, the bestscanning region, the optimal number of sensors, etc. All these studiesvariations have the same objective, to develop a robust and accuratemodel for the blend uniformity monitoring.


IN-DEPTH FOCUS: NIR

Fishbone diagram with the variables that can impact the quality of the final blend

After choosing a calibration method,developing and validating a quantificationmodel, and selecting the strategy for theblend-end point determination, the finalgoal is to develop an automated systemthat con tinuously monitors the blendingprocess (e.g. API level and homogeneitystate) as well as the mixer parameters.

Continuous blendingMixing operations of particulate solids inthe pharmaceutical industry are carried outbatch-wise even when the previous orfurther process steps are continuous.Hence, the handling and storage of theblended product can lead to segregationproblems. An alternative to batch mixing iscontinuous blending. Continuous blendingaims to continuously feed and blend theingredients thus the resulting blend is ready for the next unit.

The advantages of a continuous blender include:� Reduction of intermediate handling and segregation: connecting

the continuous mixer to the previous and next unit operation is ofgreat industrial value, since segregation of the powder blend mayoccur during the handling of the final blend

� Continuous blenders can produce larger quantities of a powdermixture compared to batch mixers

� The presence of axial and radial mixing together with betterdispersion of the minor components lead to a better mixed product

� Reduction of storage space: this is only feasible when the blender isconnected to the previous or next processing step

� Automatic control: allows for the correct monitoring of the processparameters, such as stirring rate, mass flow rate, feeding rate ofeach ingredient

� Easier scale-up: can be achieved by extension of the blender total runtime

IN-DEPTH FOCUS: NIR

Figure 2: Example of NIR spectrometer position in batch blending process (a) and in a continuous blending process (b)

Test a publisher’s statement of circulation. In today’s

business climate you can’t afford not to.

Our ABC Certificate provides accurate, independently

verified circulation figures, giving you confidence in

your advertising investment.

For more information visit www.abc.org.uk

or email [email protected]

If you want to reach 11,9991 total average net circulation,

then call Andrew Johnson on +44 1223 345 600

or email [email protected]

1. Circulation figure relates to period from 01/01/2013 to 31/12/2013

� Faster product availability by using a PAT tool: real-time monitoringof the process would provide a valuable way of measuring the APIlevel as a quality attribute. Additionally, the product would alreadybe tested once it arrives at the next unit operation

� Reduce the analytical time and sampling: this can be achieved witha non-invasive spectroscopic technique such as NIR, so therequirements of reagents and off-line analytical tests are skipped

� Lower production and analytical costs: the continuous productioncombined with a suitable PAT tool can dramatically reduce the amount of off-line tests and production costs, although thecontinuous blender, feeding system, PAT equipment, andautomation costs can be higher than in a batch system

� Less labour work: minimum operator work is needed since fillingand emptying is done automatically and sampling can be avoided.

By using NIR spectroscopy for the in-line monitoring of powder stream the powder (or pharmaceutical blend) is analysed withoutdisrupting the process, the sampling stage is eliminated, and the highrate of measurements performed.

Continuous blending also holds some disadvantages. Usually thecontinuous blender is product-specific and switching to anotherproduct is not a simple process. Also, the breakdown of the equipmentor the malfunctioning of the feeding system can stop the productionchain. In the pharmaceutical industry, the definition of a batch in acontinuous process needs to be clearly specified. The feeding system needs to be accurate and reliable. Calibration of the equipment,mostly of the feeding system, requires careful and narrow ranges.

Cohesive powders can be challenging for the feeding system. If theremoval of samples is required, it must be done with a good samplingprocedure in order to avoid biased and misleading results. If the controltechnique includes a MVDA method, this needs to be reliable andaccurate as well. The automation system has to react quickly to anyprocess deviations.

The monitoring of a continuous blending is performed at the outlet of the blender when the blend is forming a powder stream(see Figure 2, page 59), the majority of industrial chute applicationsinvolve rapid or accelerated flow conditions in which a ‘thin’ stream ispresent, where the thickness of the powder bed is less than the widthof the chute, under these conditions the powder will have a velocityprofile. Particle velocity can present artifacts on the spectral data,influencing the quality of the results. It is important to point out thatthe mass flow rate as well as velocity variations will influence theinteraction of the NIR radiation with the sample, which will impact the amount of powder seen by the NIR probe. The study of granularmaterials flow is a complex task where particle size, angle of repose,particle interactions, and process conditions such as chute design arerelevant for the final flow of the particles. In addition, the processparameters such as stirring rate and feeding rate must be consideredduring the development of the calibration model. The complexity of thegranular flow as well as the kinematic, physical and chemicalinformation contained in the NIR spectroscopic data pushes to a carefulanalysis of the results, where chemometrics has a key role for thesuccessful development of a multivariate model.

ConclusionsScientific community, pharmaceutical industry and health authoritieshave shown great interest in NIR spectroscopy as tool for themonitoring of pharmaceutical operations such as blending of powders.NIR spectroscopy is increasingly becoming a common tool for processmonitoring and control, which leads to the better understanding and improvement of the mixing processes. The high benefits associ-ated to the implementation of NIR as a PAT tool, has lead to a lot ofresearch focused on the development of robust and reliable models for the quantification or monitoring of the parameter of interest, such as API levels.

NIR spectroscopy has been succesfully implemented for the real-time monitoring of batch-wise and continuous mixing processes. A good understanding of the critical parameters leads to a robust process and reliable analytical methods. NIR proved to be a valuable and versatile analytical tool in the real-time measurement of bulk solids.

IN-DEPTH FOCUS: NIR


Lizbeth Martinez holds a PhD in Pharmaceutical Tech -nology from the University of Basel in Switzerland. Her research has been focused on the implementation ofnear-infrared spectroscopy for the real-time monitoring of pharmaceutical processes. Since June 2011, Lizbeth hasbeen working for Novartis Switzerland. She is an expert incombining physical-pharmacy with chemometrics for the

better understanding of pharmaceutical processes. Lizbeth has been applyingquality by design concepts for process validation and process analyticaltechnologies for monitoring and control of batch and continuous processes.

1. International Conference on Harmonization, ICH Q8 (R2), 2009. PharmaceuticalDevelopment.http://www.ich.org/fileadmin/Public_Web_Site/ICH_Products/Guidelines/Quality/Q8_R1/Step4/Q8_R2_Guideline.pdf, accessed April 2014.

2. FDA, 2004. Guidance for Industry: PAT – A Framework for Innovative PharmaceuticalDevelopment, Manufacturing, and Quality Assurance. http://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/ucm070305.pdf,accessed April 2014.

3. Cuesta-Sánchez, F., Toft, J., van den Bogaert, B., Massart, D.L., Dive, S.S., Hailey, P.,1995. Monitoring powder blending by NIR spectroscopy. Fresenius J. Anal. Chem. 352, 771-778.

4. El-Hagrasy, A., Morris, H.R., D’Amico, F., Lodder, R.A., Drennen III, J.K., 2001. Near-Infrared Spectroscopy and Imaging for the Monitoring of Powder Blend Homogeneity. J. Pharm. Sci. 9, 1298-1307.

5. Puchert, T., Holzhauer, C.-V., Menezes, J.C., Lochmann, D., Reich, G., 2011. A new PAT/QbD approach for the determination of blend homogeneity: Combination ofon-line NIRS with PC Scores Distance Analysis (PC-SDA). Eur. J. Pharm. Biopharm. 78, 173-182.

6. Wargo, D.J., Drennen, J.K., 1996. Near-infrared spectroscopic characterization ofpharmaceutical powder blends. J. Pharm. Biomed. Anal. 14, 1415-1423.

7. Blanco, M., González-Bañó, R., Bertran, E., 2002. Monitoring powder blending inpharmaceutical processes by use of near infrared spectroscopy. Talanta 56, 203-212.

8. Flåten, G.R., Ferreira, A.P., Bellamy, L., Frake, P., 2012. PAT within the QbD Framework:Real-Time End Point Detection for Powder Blends in a Compliant Environment. J. Pharm. Innov. 7, 38-45.

9. Sekulic, S.S., Ward II, H.W., Brannegan, D.R., Stanley, e.D., Evans, C., Sciavolino, S.T.,Aldridge, P.K., 1996. On-Line Monitoring of Powder Blend Homogeneity by Near-Infrared Spectroscopy. Anal. Chem. 68, 509-513.

10. Andersson, M., Svensson, O., Folestad, S., Josefson, M., Wahlund, K.-G., 2005. NIRspectroscopy on moving solids using a scanning grating spectrometer-impact onmultivariate process analysis. Chemometr. Intell. Lab. Syst. 75, 1-11.

11. Karande, A.D., Liew, C.V., Heng, P.W.S., 2010. Calibration sampling paradox in near infrared spectroscopy: A case study of multi-component powder blend. Int. J. Pharm. 395, 91-97.

References

A well-established and widely-used method for quantitative elementalanalysis is ICP-AES (Inductively Coupled Plasma – Atomic EmissionSpectroscopy). Although powerful and efficient, this technologydepends on many consumables and has several drawbacks, such as

sample preparation requiring long acid digestions, which poses healthand environmental risks. Many alternative spectroscopic techniqueshave been developed for elemental quantification, and couldpotentially replace ICP-AES. This is the case of LIBS (Laser Induced

Pharmaceutical product manufacturing is a conservative environment because of the obligations to abide byrigorous operation protocols aimed at insuring the highest possible product quality. A relatively recent initiative-guidance, from the U.S. FDA (Food and Drug Administration) has encouraged innovation and development of PATs (Process Analytical Technologies) for improved process efficiency1. This has created opportunities fortechnological development and application of available technologies.

Novel methodologies fordetermining the mineralcontent of complexmultivitamin tablets

Ryan Gosselin and Nicolas AbatzoglouPfizer Industrial Research Chair, University of Sherbrooke

Philip QuinnPfizer Industrial Research Chair, University of Sherbrookeand Process Analytical Sciences Group, Pfizer Canada

Joanny Salvas and Jean-Sébastien SimardProcess Analytical Sciences Group, Pfizer Canada


X-RAY FLUORESCENCE

© c

harle

s tay

lor /

Shu

tter

stoc

k.co

m

Breakdown Spectroscopy) developed over the last 50 years2,3 and XRF (X-Ray Fluorescence), which has been used in the mining andmetallurgy industry for many years4,5.

Furthermore, LIBS has already been present for some time inpharmaceutical research for its potential for 3-D profiling due to itsmicro-destructive nature6. Tablet coating thickness and uniformity hasalso been assessed using this technology by applying multipleconsecutive laser shots to a tablet until its core’s spectral signature isrevealed7,8. Many other LIBS efforts applied to the pharmaceuticalindustry were for the classification9 and quantification10-12 of minerals inpharmaceuticals. These papers show that LIBS has proven effective formicroscopically homogeneous samples, but the work done on micro-heterogeneous complex samples, such is thecase for pharmaceutical multivitamin tablets isnot as common.

Likewise, XRF is another elemental analysistechnology in which pharmaceutical researchhas increasing interest. Several research effortsdemonstrate its applicability for the identification of the presence ofimpurities in pharmaceutical tablets13,14. Micro-confocal XRF was used tostudy elemental distributions in tablets, up to a few hundred micronsdeep15. Contrarily to other industry branches and activities that havelower scrutiny levels, such as Food & Nutrition, Mining & SolidEngineering, few quantification applications of this technology in apharmaceutical context are presented in the literature.

The objective is to assess the potential of XRF and LIBS for at-line

mineral quantification in multivitamin tablets. Ten elements, varying inconcentration from traces to major components (< 10 ppm to > 30%),are targeted in this study: Mg, K, Ca, V, Cr, Mn, Fe, Cu, Zn and Mo.Methodology includes the use of univariate and multivariate analysis techniques.

Material and methodsLIBS instrumentLIBS analysis is based on plasma emission spectroscopy and consists ofablating a sample with a high-powered laser. The resulting plasmacondenses and emits light that is characteristic of the sampleelemental composition. This light is collected with an optical fibre andthe signal is transferred via appropriate optical hardware for conversioninto a spectrum. The LIBS instrument used for the experiments is a TSI Insight 2012 equipped with a high sensitivity gated iCCD camera (16-bit, UV-enhanced), an Echelle spectrometer (200-1000 nm range)and a 200 mJ Nd:YAG laser (1064 nm, adjustable from 0-100% laserenergy). Data was analysed using both the instrument supplier software(AddLIBS) for the spectral line database and Matlab (MathWorks) codesfor modelling and data treatment.

XRF instrumentXRF is a technology based on the fluorescence phenomenon. It con-sists of bombarding a sample with X-rays that will eject inner shell electrons of the elements present in the sample. The resulting

vacant spots will be filled by outer shellelectrons and will emit the energy difference of the transition quantum states as a photon. The energy of the photons is characteristic of the elements; they are collected and theirenergy spectrum is analysed.

The XRF instrument used for the experiments is a PANalytical AxiosWD-XRF equipped with a Rh-anode Super Sharp Tube (1 kW, 20-60 kV, 16-50 mA), a DOPS goniometer, 11 interchangeable crystals, a gas flowproportional counter and scintillation detector.

Sample preparation and reference methodThe tablets tested were composed of over 35 pharmaceuticalingredients with typical concentrations of commercial multivitamin

X-RAY FLUORESCENCE


Table 1: Qualitative concentrations for multivitamin tablets

Elements Concentration range

Ca Major

K Major

Mg Major

Zn Minor

Fe Minor

Mn Minor

Cu Trace

Cr Trace

Mo Trace

V Trace

Table 2: XRF results from univariate and multivariate data analysis methods

MEP (%) MEP (%) R2 cal R2 cal

Element univariate multivariate Nb. LVs VIP univariate multivariate R2 val

Mg 7 10 10 Mg, Na, Fe 0.80 0.98 0.58

K 27 18 8 K, Cl, B, Mg 0.33 0.96 0.82

Ca 8 6 3 None above 2 0.57 0.85 0.63

V 20 25 6 V 0.77 0.87 0.35

Cr 30 16 6 Cr, Zn, Cu 0.65 0.85 0.90

Mn 8 12 8 Mn, Zn, Cu, S, P 0.91 0.99 0.89

Fe 9 8 11 Fe, Zn, Cu, Si, Na 0.89 0.99 0.40

Cu 13 19 11 Cu, Zn, Fe, Mn, Na 0.90 0.99 0.86

Zn 12 19 5 Zn, Cu, Fe, Na 0.56 0.95 0.05

Mo 18 17 9 Mo 0.87 0.97 0.82

Mean 15 15 NA NA 0.73 0.94 0.63

p-value 0.48 NA NA 8.2E-04 NA

LIBS has already been present for some time in pharmaceutical researchfor its potential for 3-D profiling due to

its micro-destructive nature

tablets. For confidentiality reasons, only concentration ranges of the 10 elements of interest for this study are presented in Table 1 (page 63), so:� Major components: concentration > 1% (wt/wt)� Minor components: 1% (wt/wt) > concentration > 0.1% (wt/wt)� Trace components: concentration < 0.1% (wt/wt).

For XRF, the calibration dataset was composed of 11 formulations: 10 formulations prepared at lab scale and one commercial sample. For LIBS, the calibration dataset was composed of 10 formulationsprepared at lab-scale. All elemental concen -trations varied between 50% and 300% ofcommercial product label claim.

Verification sets for XRF and LIBS werecomposed of four formulations: three lab scaleand one commercial. Lab formulations were prepared in order to obtainmineral concentrations varying in the calibration range. Formulationswere homogenised using a Retsch mixer mill with a single stainless steel ball and compartment for one minute at 50% amplitude. Tablets were compressed using a manual press at 25,000 psi for approxi -mately 45 seconds.

The chosen reference method for elemental concentrations wasICP-MS. The sampling for ICP-MS was done after tablet compression toavoid segregation caused by sample manipulation. For the formulationspreparation, care was taken to minimise correlations between thevarious elemental concentrations. The highest correlation obtained is0.39 between Fe and Mg which means that a low correlation is presentamong all minerals.

SamplingSampling protocols were adapted to each technology considering thevarying sample sizes. Two 7g tablets of each formulation were preparedaccording to the sample preparation method.

For XRF testing, the two tablets were tested on both sides for a total of four samplings per formulation. In the case of LIBS, the numberof shots required for significant sampling of each tablet wasdetermined by a Monte Carlo simulation of the sampling process. The sampling template proposed is a seven (length) x six (width) x seven(depth) shot matrix.

Acquisition parametersXRF acquisition parameters used were those suggested by theinstrument provider software and varied for each element.

The optimal acquisition parameters for LIBS were determined by afull factorial experimental design (DoE) with centre points thatoptimised the signal-to-noise ratio for each element. The plan variedfour factors: laser power, gate delay, gate width and spot size. The design results showed that all elements of interest had similaroptimal parameters and thus the following were used: laser power at

75%, gate delay at 3.7μs, gate width at 15μs andspot size at 500μm.

Data analysisA univariate analysis method was compared to

a multivariate approach. The univariate analysis was done by correlatingelemental peak intensities with their theoretical concentration. The highest intensity peak free from any overlapping peaks was chosenfor the univariate analysis. In the multivariate approach, PLS modelswere built for each element and each instrument. The number of latentvariables was chosen by minimising the error of prediction whileseeking to limit the number of latent variables used by the model.

For the evaluation of model performance, several criteria wereused. Mean error of prediction (MEP) was calculated to assessprediction error and the determination coefficient (R2) was used tocompare linearity. For multivariate models, linearity of the predictiondata was also investigated. Finally, variable importance in theprojection (VIP) values represent the variables that were most influenton the prediction. Thus, they contain information regarding modelrobustness for the analyst by linking these variables with potentialcause-effect linkages. All presented p-values correspond to paired one-tailed t-test results.

XRF data analysisMultiple XRF peaks were compiled for the analysis. All lines were chosento maximise signal intensity without overlapping with lines of otherelements in the formulation. A total of 33 XRF line intensities werecollected with their respective baselines, yielding a data matrix of 29 observations x 66 variables.


X-RAY FLUORESCENCE

XRF is another elemental analysistechnology in which pharmaceutical

research has increasing interest

Table 3: LIBS results from univariate and multivariate data analysis methods

MEP (%) MEP (%) R2 cal R2 cal

Element univariate multivariate Nb. LVs VIP univariate multivariate R2 val

Mg 16 10 2 no peak (283.10 nm) 0.36 0.55 0.89

K 43 36 6 P (253.66 nm) 0.27 0.86 0.19

Ca 10 16 6 Si (288.16 nm) 0.53 0.88 0.08

V 213 94 5 no peak (438.02 nm) 0.07 0.63 0.07

Cr 41 20 2 no peak (286.44 nm) 0.44 0.54 0.84

Mn 15 39 9 unidentified peak (482.46 nm) 0.77 0.97 0.76

Fe 45 7 5 Si (288.16 nm) 0.04 0.66 0.17

Cu 67 24 10 Cu (327.40 nm) 0.23 0.97 0.58

Zn 70 4 5 Cr (425.43 nm) 0.01 0.72 0.76

Mo 73 50 3 no peak (589.90 nm) 0.12 0.49 0.40

Average 59 30 NA NA 0.28 0.73 0.47

p-value 0.023 NA NA 9.2E-05 NA

© A

ndre

y Yu

rlov

/ Shu

tter

stoc

k.co

m

D I R E CTO RY

Visit www.europeanpharmaceuticalreview.com/directory

LIST YOUR COMPANY

FREE OF CHARGE

Increase your company'sprofile, drive traffic to yourwebsite and boost yoursearch engine ranking…List your company FREE of charge on European PharmaceuticalReview’s company directory!

With its extensive listing of detailed company profiles, the European Pharmaceutical Reviewonline business directory providesindustry professionals with a unique and powerful tool from which to promotetheir products and services.

Its advanced search engine makes it easy to find information about a listedcompany in the pharmaceutical industryand look for a supplier, producer orpartner. Either enter a name into thekeyword search box or use our categorysection to locate the supplier you need.

Showcase your solutions and capabilities.

Join our FREE company directory today!

© J

ohan

Sw

anep

oel /

Shu

tter

stoc

k.co

m

LIBS data analysisAll LIBS spectra for each analysed tablet were averaged for a total of 252 samples per observation, yielding a data matrix of 29 observations x 40,002 variables. Resulting spectra were normalized for total lightaccording to Equation 1.

Equation 1: Total light normalisation equation for LIBS spectra

Where var(i) is the variable i, var_norm(i) is the normalised variable iand nb.vars is the total number of variables in the spectrum. Followingtotal light normalisation, Standard Normal Variate (SNV) andautoscaling algorithms were applied to thedata. An SNV algorithm consists in anobservation-wise standardisation that divideseach variable by the observation mean.Similarly, an auto-scaling consists in a variable-wise standardisation inwhich the variable mean is subtracted from each observation anddivided by its standard deviation.

Results and discussionXRF resultsTable 2 (page 63) shows XRF results obtained from univariate andmultivariate analysis methods. Univariate model performance seems to

be highly dependent upon elemental nature and concentration. Low concentration elements tend to have higher prediction errors sincetheir concentrations approach the theoretical quantification limit of theequipment. On the other hand, linearity does not seem to be linked toelemental concentration with major elements like K, showing lowlinearity of the calibration curve.

Figure 1 a and c show examples of XRF univariate and multivariatecalibration curves for typical elements with good performance results. Amultivariate model has the potential to take into account someelemental interactions (i.e. matrix effects). This can be seen in the VIPsfor each model and the high number of latent variables required tominimise the prediction error. The element of interest is always one ofthe major VIPs in the model but other spectral lines are used for

the prediction; this means that there is apossible interaction between these elements.As previously explained, correlations betweenknown elemental concentrations were mini -

mised, limiting the possibility that these correlations are the cause ofthese VIP observations (some elements are of unknown concentrationsin the samples i.e. Na).

Calibration data is much more linear than verification sets; thiscould be explained by the fact that, in many cases, concentrations inthe verification set cover a narrower range. Also, fewer samples arepresent in the prediction set which could influence linearity.

At a confidence level of 95%, it is possible to conclude that neither


X-RAY FLUORESCENCE

XRF is a technology based on thefluorescence phenomenon

Figure 1: (a) Minor element (Mn) univariate calibration curve showing a good prediction error and good linearity, (b) Minor element (Mn) univariate calibration curveshowing a fair prediction error and fair linearity, (c) Major element (Mg) multivariate calibration and prediction curves showing a good prediction error and good linearity and (d) Trace element (Cr) multivariate calibration and prediction curves showing a fair prediction error a

of these two approaches (i.e. univariate or multivariate), seems toperform better when it comes to its prediction error (p = 0.48). In contrast, calibration curve linearity is significantly superior inmultivariate models (p = 8.2E-4).

LIBS resultsResults obtained with the LIBS technology are presented in Table 3(page 64). For the method, the univariate approach yields significantlyinferior prediction performance when compared to the multivariateapproach (p = 0.023). The same conclusions are obtained whencomparing both analysis methods based on linearity (p = 9.2E-5).Nevertheless, multivariate models do not seem to be robust since mostof them have VIPs based on spectral areas that have no peaks or thatpresent peaks of other elements.

Figure 1 b and d (page 66) show examples of LIBS univariate and multivariate calibration curves for typical elements with good performance results. Univariate analysis probably performs

poorly due to significant matrix effects. This is plausible because there are important variations in the matrix composition from sample to sample. The matrices vary significantly in organic andinorganic compositions, whose thermal properties may influenceplasma formation and emission intensity making it difficult to correlate line intensity with concentration. For the multivariate analysis, such a high dimensionality (40,002 variables) increases theprobability of having correlations between noise in the data and the reference values. This can explain why so many VIP valuescorrespond to spectral areas that are not theoretically linked to theelement in question.

In general, multivariate models perform better in the case of LIBSbased on the two proposed criteria, but much improvement is neededprior to a pharmaceutical industrial application.

Overall comparison of the technologiesIn order to compare both instruments, only multivariate model resultswill be taken into account. With an average error of prediction near 15% for XRF and close to twice that for LIBS, XRF should be consideredas the better alternative for mineral quantification in pharmaceuticalmultivitamin tablets (p = 0.038). Moreover, calibration models tend tobe much more linear with XRF (p = 0.002).

For other types of applications, it is important to consider the other attributes of these two techniques to properly determine which is more suitable.

Table 4 is provided for comparison of qualitative instrumentattributes. These attributes render the instruments applicable in

X-RAY FLUORESCENCE

Table 4: Qualitative attribute comparison between XRF and LIBS

Attribute LIBS XRF

Mapping 3D No mapping

Can analyse all elements? Yes No (Z > 10-12)

Required sample quantity micrograms grams

Sample preparation None Minutes

Destructive? Micro-destructive Generally not

Size of sampling μm2 cm2

At-line potential? Yes Yes

Network online with your industry peers, visit:

http://linkd.in/PharmaReviewMembers and non-members are welcome to join the discussions

LET’S CONNECT!

Exchange information, ideas and opportunities

different situations and therefore should be considered along withquantification performance results.

ConclusionTwo novel technological applications, XRF and LIBS, were evaluated toassess their potential to replace laborious traditional elementalanalysis instruments for mineral quantification in pharmaceuticalmultivitamin tablets.

XRF provides lower prediction error and better linearity in thecalibration curves. When comparing data analysis methods, neithermultivariate nor univariate stands out as a better method for XRF. For simplicity reasons, the univariate approach is, thus, recommended,at the present state of the method’s development.

It could also be a solution to take advantage of both analysismethods to improve performance. Since one model is generated perelement, it would be advantageous to choose specific analysis methods

for each element which would be specific to model interactions or takeinto account element concentration ranges.

Furthermore, even though LIBS has not yet proven to perform aswell as ICP and XRF in the studied case of mineral quantification incomplex and heterogeneous multivitamin tablets, we are still well away from a final conclusion regarding its usefulness for pharma -ceutical applications. On the contrary, it is a technology that offersmuch potential for 3D mapping of minerals in heterogeneous samples and could prove useful in reducing sample preparationresources needs (time and cost) for quantification in homogeneous and low-complexity samples.

X-RAY FLUORESCENCE


Dr. Ryan Gosselin is an Associate Professor at theDepartment of Chemical & Biotechnological Engineeringof the Université de Sherbrooke, Canada. He is a specialistin Process Engineering and on-line quality monitoringthrough the use of multivariate data analysis andchemometrics. As a member of the Pfizer IndustrialResearch Chair on Process Analytical Technologies (PAT) in

Pharmaceutical Engineering, Ryan’s present work focuses mainly on issuesrelating to the production and handling of non-reactive particulate systems.Email: [email protected].

Nicolas Abatzoglou is a Full Professor and served as Headof the Department of Chemical & BiotechnologicalEngineering of the Université de Sherbrooke (2008-2012).He is an Adjunct Professor, University of Saskatchewan,Department of Chemical Engineering and presentlyVisiting Professor, Department of Chemical Engineering ofthe École Polytechnique de Montréal. Nicolas is a specialistin Process Engineering involving Thermochemical & Catalytic Conversionas well as Particulate Systems, and Director of the Research Centre GREEN-TPV (Groupe de Recherche en Énergie/Environnement-Technologies etProcédés Verts). Since May 2008, Nicolas is the holder of the Pfizer Chair in Process Analytical Technologies (PAT) in Pharmaceutical Engineering.

Philip Quinn is completing a M.Sc.A. in ChemicalEngineering with the Université de Sherbrooke as part of thePfizer Industrial Research Chair on Process AnalyticalTechnologies (PAT) in Pharmaceutical Engineering. Hisresearch goals are to develop rapid analytical methods forAPI quantification in pharmaceutical tablets usingmultivariate predictive models. Philip has a Bachelor’s

degree in Biotechnological Engineering and his Master’s degree is beingcompleted at Pfizer Montreal’s facility (Canada) as a PAT project leader fortechnology transfer and development.

Joanny Salvas has a Bachelor’s degree in biotechnologicalengineering. She has completed a M.Sc.A. in ChemicalEngineering with the Université de Sherbrooke, conductingher graduate work at Pfizer Montreal’s facility (Canada), aspart of a Chair partnership. Her research is aimed atoptimising the development protocol of multivariatepredictive models used as part of PAT methods. Joannycurrently is a PAT Sr Scientist at Pfizer Montreal, where she pursues severalprojects with different technologies such as Raman spectroscopy and RapidMicrobiological Methods. She is also leading projects for international sites.

Jean-Sébastien Simard is Senior Manager/Team Leaderlocated in Montreal, Canada. He has a Bachelor and aMaster’s degree in Chemical Engineering from Universitéde Sherbrooke. He is currently pursuing a MBA degree atUniversité Laval in Québec, Canada. He started in 2002with Wyeth Canada where he worked as a Product andProcess Development Scientist for the pharmaceutical

processing unit. Jean-Sébastien then became responsible for the ProcessAnalytical Technology Development Group of the Technical Services inMontréal, and he now leads a team that supports the implementation of PATacross all sites in Pfizer’s Consumer Health and Local Markets operatingunits. Jean-Sébastien is also the Industrial Responsible of the Université deSherbrooke/Pfizer Industrial Research Chair on Process AnalyticalTechnologies in Pharmaceutical Engineering.

1. FDA. Guidance for industry PAT — A framework for innovative pharmaceuticaldevelopment manufacturing, and quality assurance. 2004:1.

2. Radziemski LJ. From LASER to LIBS, the path of technology development.Spectrochimica Acta – Part B Atomic Spectroscopy. 2002;57:1109.

3. ICET. LIBS2010-6th international conference on laser induced breakdown spectroscopy.http://www.icet.msstate.edu/libs2010/LIBS2010_Technical_Program_16July.pdf.Updated 2010. Accessed avril/19, 2012.

4. Robertson MEA, Feather CE. Determination of gold, platinum and uranium in southafrican ores by high-energy XRF spectrometry. X-Ray Spectrom. 2004;33(3):164-173.

5. Guo S-, Ge L-, Lai W-. XRF technique for rapid determination of fe ti content of fe ti- metal ore concentrates. Wutan Huatan Jisuan Jishu. 2007;29(5):436-438.

6. St-Onge L, Archambault J-, Kwong E, Sabsabi M, Vadas EB. Rapid quantitative analysisof magnesium stearate in tablets using laser-induced breakdown spectroscopy. Journal ofPharmacy and Pharmaceutical Sciences. 2005;8(2):272-288.

7. Madamba MC, Mullett WM, Debnath S, Kwong E. Characterization of tablet filmcoatings using a laser-induced breakdown spectroscopic technique. AAPSPharmSciTech. 2007;8(4).

8. Dubey A, Keyvan G, Hsia R, et al. Analysis of pharmaceutical tablet coating uniformityby laser-induced breakdown spectroscopy (LIBS). Journal of Pharmaceutical Innovation.2011;6(2):77-87.

9. Myakalwar AK, Sreedhar S, Barman I, et al. Laser-induced breakdown spectroscopy-based investigation and classification of pharmaceutical tablets using multivariatechemometric analysis. Talanta. 2011;87(1):53-59.

10. St-Onge L, Kwong E, Sabsabi M, Vadas EB. Quantitative analysis of pharmaceuticalproducts by laser-induced breakdown spectroscopy. Spectrochimica Acta – Part B AtomicSpectroscopy. 2002;57(7):1131-1140.

11. Arantes De Carvalho GG, Nunes LC, Florêncio De Souza P, Krug FJ, Alegre TC, SantosJr. D. Evaluation of laser induced breakdown spectrometry for the determination of macroand micronutrients in pharmaceutical tablets. J Anal At Spectrom. 2010;25(6):803-809.

12. Lewen N. The use of atomic spectroscopy in the pharmaceutical industry for thedetermination of trace elements in pharmaceuticals. J Pharm Biomed Anal.2011;55(4):653-661.

13. Marguí E, Fontàs C, Buendía A, Hidalgo M, Queralt I. Determination of metal residues inactive pharmaceutical ingredients according to european current legislation by using X-ray fluorescence spectrometry. J Anal At Spectrom. 2009;24(9):1253-1257.

14. Arzhantsev S, Li X, Kauffman JF. Rapid limit tests for metal impurities in pharmaceuticalmaterials by X-ray fluorescence spectroscopy using wavelet transform filtering. AnalChem. 2011;83(3):1061-1068.

15. Mazel V, Reiche I, Busignies V, Walter P, Tchoreloff P. Confocal micro-X-rayfluorescence analysis as a new tool for the non-destructive study of the elementaldistributions in pharmaceutical tablets. Talanta. 2011;85(1):556-561.

16. Kim K-, Kim G, Kim J-, Park K, Kim K-. Kriging interpolation method for laser inducedbreakdown spectroscopy (LIBS) analysis of zn in various soils. J Anal At Spectrom.2014;29(1):76-84.

References

CPhI Worldwide – together with co-locatedevents ICSE, InnoPack, and P-MEC – offersproducts and services catered to specificsectors of the pharmaceutical manufactur-ing market, covering the entire supply chain. The expanded exhibition makes the event themost effective and efficient place to makevaluable business connections.

Complete supply chain sourcing in at one eventCPhI Worldwide, along with three co-locatedevents, provide attendees with access tosuppliers across every aspect of the supplychain including pharma ingredients, outs -ourced services, packaging, and technologyand equipment.

Whilst CPhI focuses primarily on pharmaingredients with exhibitors covering ingredi -ents, APIs, excipients, fine chemicals andintermediates, and more, co-located showICSE is a dedicated outsourcing eventdesigned to connect the pharmaceuticalcommunity with contract service providersincluding specialist CRO & (pre)clinical trialcompanies, logistics and cold chain providers,and bioservices companies. P-MEC deliversinnovative pharmaceutical machinery,equipment and technology to a worldwideforum of decision-makers and incorporatesLABWorld for laboratory, analytical andbiotechnology instrumentation. The final co-located event is InnoPack which offers thepharma community innovative and diversepackaging solutions to satisfy the changingway we package and deliver medication.

A zone-based layout at CPhI and co-located events will make your search for theright business partners much easier.Reflecting the current trends within thepharma industry, the zones in each exhibit areadjusted annually to meet the needs of allattendees, providing the opportunity tosource suppliers for their latest needs.

Given the increase in outsourcing andnecessity of strategic investment, CPhIundoubtedly provides the best opportunity togenerate partnerships and business leads thatwill drive business for the short and long-term. CPhI is the networking event for anybusiness in the pharmaceutical machinery,equipment and technology industry.

Celebrating 25 years of CPhICPhI has been instrumental in bringingtogether businesses in order to advance thepharmaceutical industry and initiate businessgrowth. 2014 marks 25 years of CPhI World -wide’s success in fostering innovation andpartnerships. To mark this special anniversary,CPhI requested that past participants submittheir success story, highlighting how CPhI wasa catalyst for initiating growth and achievingbusiness goals.

Highlighting exhibitors and attendees who made valuable connections through CPhIWorldwide, 25 success stories will be featuredin a special anniversary publication availableafter the event. During the exhibition one ofthese success stories will be on display, while additional success stories will be filmedat the exhibition on 7 October 2014. These

short films will be on display at www.cphi.comafter the event.

To continue the celebration, CPhI will hosta 25th Anniversary Networking Event on 8 October 2014 complete with hors d’oeuvres,cocktails and entertainment which will takeplace in the luxurious InterContinental Paris LeGrand, overlooking the world famous ParisOpera and providing an exclusive opportunityto network with top industry professionals.

New developments for 2014Annual ReportThe CPhI Annual Report, in its second year,features a collection of in-depth essays fromthe 13 member expert panel. Part 1 of thereport will be launched in the press ahead ofthe show (September 2014) with part tworeleased during show.

CPhIChat: facilitating debates around the future of pharmaFollowing the release of CPhI’s Annual Report,the inaugural CPhIChat will take place on thefirst day of CPhI Worldwide from 2-4pm. The ‘Future of Pharma’ is central to the dis -cussion, building on expert forecasts found inthe CPhI Annual Report. Industry profess -ionals and media are invited to participate inthe inaugural – a first of its kind globalindustry-wide – Tweetchat.

CPhI Chat topics will centre on the ‘Futureof Pharma’, providing the industry and mediawith a platform for discussing key trendsaffecting the industry including the imple -mentation of QbD, innovation and IPR, green

This year, more than 34,000 attendees and 2,500 exhibitors from more than 140 countries will converge at CPhI Worldwide and co-located events for three days. The event will take place at the Paris Nord Villepinte in Francefrom 7-9 October 2014. There, senior pharma professionals with global pharmaceutical suppliers and buyers willgather under one roof to collectively drive business and innovation in the global pharmaceutical industry.

SHOW PREVIEW: CPhI WORLDWIDE 2014

Celebrating 25 years of fosteringsuccessful pharma partnerships


chemistry, excipient risk analysis andincreased outsourcing. Media, industryprofessionals, and experts will then be askedto weigh-in on the discussion and proposeadditional relevant questions, promotingthought-provoking conversations.

The debate will be streamed in real-timeon the display screens throughout theexhibition, with a summary report releasedafter the show. Alternatively, the debate canbe followed by searching for the hashtags onTwitter from anywhere in the world.

To join the debate, participants can loginto Twitter from 2-4pm on 7 October 2014 anduse the hashtags #CPhIChat and #CPhIWWwhen commenting.

Women’s Networking Breakfast In 2013, 24% of women globally held seniorleadership roles, up 5% from 2004. Thiswelcome growth in diversity is expected to continue. To celebrate, CPhI Worldwidehosts its first annual Women’s NetworkingBreakfast, providing an inspirational morningof networking education and empowermentfor women in the pharmaceutical industry on8 October 2014 at Villepinte Paris.

Women from across the pharmaceuticalindustry will have the opportunity to hearempowering messages from some of thepharmaceutical industry’s female thought-leaders, as well as an inspirational programmeby our partner charitable organisation, Global Angels. Ample time will also beallocated for networking and creating conn -ections within the pharmaceutical industry’scommunity of women.

Conferences and seminarsIn addition to attending the exhibition, CPhIworldwide offers conferences and seminars,introducing attendees to industry trends andoffering in-depth sessions. The Pre-ConnectCongress and new InnoPack Conference bothtake place on 6 October 2014, leading up to theexhibition. These pre-show events offer the exclusive opportunity to join seniorexecutives and influential speakers fromacross the pharma industry in networking andstrengthening your knowledge base on avariety of key topics such as packaginginnovation, strategic partnerships, and drugdelivery systems.

The Pre-Connect Congress offers eightmodules across both commercial and

technical tracks, including three new moduleson Excipients, Biopharmaceuticals, and Trends in Oncology, whilst the new InnoPackConference focuses on design trends,innovation, security, and compliance inpharma packaging and labelling. Thought-leaders will discuss topics including globalserialisation and traceability requirementsand their effects on supply chain security, aswell as innovative packaging design that assistwith patient usability and adherence.

Taking place throughout the three-dayexhibition, the new CPhI Pharma InsightBriefings offer in-depth sessions on specialisttopics, such as Drug Discovery Partnershipsand Cool Chain & Temperature Logistics, andregional updates on specific marketsincluding Brazil, Turkey, India, and the U.S.Designed for individuals and suppliers whowould like to understand the challenges andopportunities in these niche areas, thesebriefings provide valuable insights forimproving business methods or developingmarket entry strategies.

Furthermore, the show features a con -stant stream of informative content on thelatest key developments via the free sessionsin the Speaker’s Corners. You will have theopportunity to hear first-hand from exhibitorsacross the globe about the latest trendswithin the pharma industry whilst also finding

out about their latest products, innovations,services and more!

CPhI Global Meetings Programme – facilitating high-quality business meetingsEvery year, over 94% of visitors make newbusiness contacts at CPhI Exhibitions. Takingplace across the three-day show, the GlobalMeetings Programme facilitates high-qualitymeetings, boosting ROI for all participants.The Global Meetings Programme providesexhibitors and attendees with direct access toindividual contacts – targeted to synergisetheir respective businesses needs.

Once registered, the official show meet -ings service is accessible prior to your arrivalat CPhI, allowing for advanced research intopotential meeting targets based on market,sub-sector and geographical location.Additionally, this service allows for pre-arranged one-to-one meetings, ensuring a fulldiary that suits your schedule.

CPhI Pharma Awards – celebratingtomorrow’s innovations todayIn their 11th year, the CPhI Pharma Awardscontinue to honour distinguished industrythought-leaders. In addition to annual awardsin ‘Formulation’, ‘Process Development’ and‘Packaging’, a new category recognising‘Innovation in Partnering’ debuts this year,which honours partnering methods, use oftechnology, unexpected outcomes and uniquepartnering practices.

Open to the entire pharma industry, theawards celebrate the most innovative anddynamic areas across the global pharmacommunity. Shortlisted company entries forthe ‘Innovation in Partnering’ Award will bepublished on the CPhI website invitingattendees and readers to vote online. Finalistsfor the three remaining categories will presenttheir innovations during the morning of the first show day (7 October 2014) to the jury, press and visitors. Winners will beannounced at a ceremony on the afternoon of7 October 2014. To learn more about theawards or to submit an award entry, pleasevisit www.cphi.com/awards.


SHOW PREVIEW: CPhI WORLDWIDE 2014

Date: 7-9 October 2014Location: Paris, FranceFor more information, please visit www.cphi.com

More than 34,000 attendees are expected at this year’sCPhI Worldwide and co-located events

Throughout the pharmaceutical industry, spray drying is recognised as an exceptionally efficient and effective way to maximise bio-availability. And no one is further ahead of the game than GEA Process Engineering.

Our GEA Niro spray drying technology gives you unmatched control and flexibility over particle engineering, with a single step continuous process that produces stable powders made to meet specific properties, such as solubility, flowability and dispersability.

For better results on any scale, look to GEA Process Engineering.

engineering for a better world

GEA Process Engineering A/SGladsaxevej 305, DK-2860 Soeborg, DenmarkPhone: +45 39 54 54 54, [email protected], www.gea.com

Maximise bio-availability with spray drying

Spray drying is a technique preferred by a growing number of pharmaceutical companiesto produce better drugs. This ultra-fast and gentle drying technology offers uniquepossibilities for designing particle characteristics and several companies are alreadybenefitting from it as an ‘enabling technology’ – to improve the performance of poorlysoluble APIs by producing an amorphous solid dispersion, to obtain controlled release ortaste-masking, or to produce advanced powders with specific properties.

For eight decades, GEA, through its GEA Niro brand, has been a pioneer in all aspectsof spray drying and has contracted and installed more than 10,000 plants worldwide.

GEA provides a full range of spray drying units and services to companies working with the development of spray dried pharmaceuticals and pharmaceutical grade products. At the GEA Niro Test Centre – the world’s largest and most advanced spray dryingtechnology centre – our vast knowledge of spray drying is available for companiesinvestigating the potential of the technology. The Test Centre includes a fully-equippedGMP Pharmaceutical Spray Drying facility approved according to European MedicinesAgency (EMA) regulations and also available for contract manufacturing.

GEA – pioneersin all aspects ofspray drying

ADVERTORIAL

© M

anue

lSch

Ã?Â?

Ã?Â?

Ã?Â?

Ã?Â¤

fer /

Shu

tter

stoc

k.co

m©

Nol

te L

oure

ns /

Shut

ters

tock

.com

© C

hris

toffe

r Haa

kans

son

/ Shu

tter

stoc

k.co

m

There have been a lot of discussions recently about rapid microbiologymethods for pharmaceutical manufacturers. How does the BDFACSMicroCount System fit into this discussion?

“The BD FACSMicroCount System is based on the proven flowcytometry principle, which has been in existence for over 50 years,”explains Rich. “Significant advances have occurred over this time, bothin terms of instrument technologies and reagents, to allow for a broadrange of applications from clinical to microbiological. The BDFACSMicroCount System allows for the detection and enumeration ofmicrobiological organisms – several thousand cells per second – earlierthan can be detected through traditional culture media methods.”

So what is the scientific principle behind BD’s FACSMicroCountSystem? Rich explains: “The BD FACSMicroCount is based on flowcytometry. A membrane-permeable nucleic acid dye is added to a microbiological sample and binds to the DNA. Additionally, a non-membrane-permeable dye is added that quenches thefluorescence of cells that are dead and no longer have an intact cellwall/membrane, along with any free-floating particles. These samplesare injected into the instrument into a fast-flowing sheath fluid. This action causes hydrodynamic focusing, which results in the injectedsample cells passing through a single focus point of a laser. The laser causes the dye to fluoresce and is measured by a detector, along with side-scatter (diffracted) light. This data is used to determinethe microbiological cell counts, and the generation of intensity plotsfor each sample.”

The BD FACSMicroCount System can provide numerous advantagesto pharmaceutical organisations. For example, in-process quality;earlier bioburden results allow early intervention and reduce the risk of compromising the future product, which is in line with QbD and PAT principles.

“Product release validation is another advantage, as theFACSMicroCount System meets regulatory requirements and offersdirect correlation with traditional methods,” says Rich. “It also offers operation cost savings by reducing raw material and finished

goods inventory related costs, as well as labour cost reductions due to the easy-to-use workflow and walk-away automation enablingflexibility of resources. And lastly the convenience of the product is agreat advantage; enabling multiple sample types and test protocols torun simultaneously.”

Rich explains that there are resources available to help pharma -ceutical manufacturing laboratories validate rapid microbiologicalmethods, such as the FACSMicroCount System.

“In addition to the feasibility, installation and qualification supportfrom BD, regulatory agencies have provided validation guidance onrapid microbiology methods, including: PDA Technical Report #33,Evaluation, Validation and Implementation of New MicrobiologicalTesting Methods; Ph. Eur. 5.1.6, Alternative Methods for Control of Micro -biological Quality; and USP <1223>, Validation of AlternativeMicrobiological Methods.”

Research has shown that the uptake of rapid microbiology methodsin the pharmaceutical industry has traditionally been slower than otherindustries, such as food, primarily due to a lack of pharmaceutical-specific applications. What has BD Diagnostics done to help solve this problem?

“Current research is showing that less than five per cent of micro -biology methods being performed by pharmaceutical manufacturersare rapid methods, compared to greater than 50 per cent in food andenvironmental industries,” reveals Rich. “When asked, the primaryreason for the lower uptake was not regulatory acceptance, but rather the lack of pharmaceutical-specific applications. To help solvethis problem, BD has spent the past few years working onpharmaceutical applications for the BD FACSMicroCount System,including water testing; raw material testing; in-process samples; stockculture enumeration; fermentation enumeration; and biologicalindicator testing.”

With a heritage spanning over 100 years, BD serves healthcare institutions, life science researchers, clinicallaboratories, industry and the general public. Headquartered in the United States and with offices in more than 50 countries across the globe, BD manufactures and sells a range of medical supplies, devices, laboratoryequipment and diagnostic products. BD’s extensive product range incorporates microbiology solutions andindustrial microbiology; molecular diagnostics; women’s health and cancer; laboratory automation; diagnostic,research and clinical systems; and sample collection.

Rich Quashne, WW ProductManager, Industrial Microbiologyat BD Diagnostic Systems, looksat the key attributes of BD’s latestmicrobial testing solution – theBD FACSMicroCount™ System.


For more information, please visit: www.bd.com

PRODUCT HUB

The BD FACSMicroCount System saves you time and improves your operational efficiency

Enables early intervention to reduce your risk

Runs multiple sample types and test protocols simultaneously

Provides easy-to-use workflow and walk-away automation

Reduces inventory related costs

Correlates directly with traditional methods

Microbiology – it’s what we do.

Find out what the BD FACSMicroCount System can do for you. Visit us on the web at www.bd.com/ds/microcount

Confidence in microbial solutions to save you time.

BD, BD Logo and FACSMicroCount are trademarks of Becton, Dickinson and Company. ©2014 BD

BD Diagnostics800.638.8663www.bd.com/ds

BD FACSMicroCount™

Rapid Microbial Enumeration and Detection System

Rapid

Multisizer 4e COULTER COUNTER for Quality ControlHigh resolution sizing, counting and size distribution of cells, particles or sub-visible particles.

Quality Assurance-Friendly System

The Multisizer 4e for QC is the newest member of the COULTER COUNTER family of high resolution particle counting, sizing and distribution products. The Quality Assurance-friendly system includes the following features:

• User-defined standard operation procedure

• Multiple security levels

• Software that enables 21 CFR Part 11 compliance

• Automated calibration and calibration verification for reliable results for both size and counts

• V-check validation package provides a comprehensive solution for today’s quality assurance requirements

• Certification program to ensure instrument performance

• Software for the processing and presentation of data for industrial, biological and quality control applications Key Features:

• Digital Pulse Processor (DPP)

• Dynamic size measurements

• Provides number, volume, mass and surface area size distributions in one measurement

• Overall sizing range of 0.2 μm to 1600 μm

• Not affected by particle color

• Increased dynamic range

• Increased resolution

• Proven technology

• Quality assurance friendly

Pharmaceutical QC

Filtration efficiency

Sub-visible particle monitoring and characterization

Bioprocessing monitoring

Food & Beverage QC

Yeast monitoring

Flavor emulsions

Monitoring particle levels

Industrial QC

Toner

Abrasives

Cosmetics

Emulsions

Beads

Powders

Beckman Coulter, the stylized logo and COULTER COUNTER are trademarks of Beckman Coulter, Inc. and are registered with the USPTO.

© 2014 Beckman Coulter, Inc.

For more information or to request a quote:

www.particle.com/cell-counter/multisizer-4e

Documents

Informatics Focus - European Pharmaceutical Review · grown systems got bigger, demonstrating the capability and commercial potential, and acting as a precursor to the Laboratory