Phacilitate Automation SIG: 2018 Report · 2019. 3. 1. · Phacilitate Automation SIG: 2018 Report 1 FOREWORD Since the inaugural Automation Special Interest Group (SIG) in 2017 the

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Phacilitate Automation SIG: 2018 Report

Phacilitate Automation SIG: 2018 Report

Contents

FOREWORD 1

Laura Rae, Event Manager, Phacilitate

CHAPTER ONE 3 What does the cell and gene industrial revolution look like?

Stephen Ward, Chief Operating Officer, Cell & Gene Therapy Catapult

CHAPTER TWO 5 Making the business case for automation: How tool providers and manufacturers decide whether to invest in automation

Dolores Baksh, Innovation Leader, Cell & Gene Therapy, GE Healthcare

Rodney L. Rietze, Director, Strategic Development and Innovation, Novartis Pharmaceutical Corporation

Kathie Schneider, Product Marketing Manager, Cell & Gene Therapy, GE Healthcare

CHAPTER THREE 8 Revisiting the ‘when’ of automation with product development and quality control in mind Brian Hampson, Vice-President, Manufacturing Sciences and Technology, Hitachi Chemical Advanced Therapeutic Solutions (“HCATS”)

Wilfried Dalemans, Chief Technical Officer, TiGenix NV

CHAPTER FOUR 11 Supply chain automation and integration

Tamie Joeckel, Head of Global Alliance, Vineti

Heidi Hagen, Chief Strategy Officer, Vineti

CHAPTER FIVE 13 Creating a ‘rational supply’ to reduce manufacturing timelines and product variability

Fergus McKenzie, PhD, CEO, SAKARTA Ltd.

CHAPTER SIX 16 Automating bioanalytics

Damian Marshall, Director, New and Enabling Technologies, Cell and Gene Therapy Catapult

Nicolas Markadieu, PhD, Analytical Development Expert, MaSTherCell

CHAPTER SEVEN 19 How do I begin to approach automation, especially where an ‘exact fit’ tool doesn’t currently exist? Behnam Ahmadian Baghbaderani, Global Head of Process Development, Emerging Technologies, Lonza

CHAPTER EIGHT 21 Ensuring bioprocess flexibility: How to choose between module or sub-module solutions

Geoff Ball, Manager, Cell Therapy, Invetech CHAPTER NINE 25 Future solution development – do we integrate or optimise first?

Mark Dudley, Senior Vice President, Bioprocessing, Adaptimmune

Faraz Siddiqui, Director of Tech Transfers and Process Excellence, Product Sciences, Kite Pharma

CHAPTER TEN 29 Decentralized manufacturing – what do the next 5-10 years hold?Hermann Bohnenkamp, VP Business Development, APAC, Miltenyi Biotec

Claudia Rössig, Director, Pediatric Hematology and Oncology, University Hospital Münster

Robert Deans, CTO, BlueRock Therapeutics

CHAPTER ELEVEN 32 Which tools, platforms and processes for genetically manipulating cells will win out in cell therapy? Calley Hirsch, Development Scientist II, CCRM

Spencer Hoover, Development Manager, CCRM

CHAPTER TWELVE 35 From factory to patient: What automated tools do we have and where are new innovations needed? Rodney Neal, Vice President, Strategic Program Management, Werum IT Solutions

Ohad Karnieli, CEO, Founder, ATVIO Biotechnology

Phacilitate Automation SIG: 2018 Report 1

FOREWORD Since the inaugural Automation Special Interest Group (SIG) in 2017 the pace of development in cell and gene therapy has accelerated at an astonishing rate, with several high profile approvals demonstrating just how sophisticated our approaches have become.

Despite the regulatory success, industrialising complex medicines continues to be a significant challenge and we need open innovation if we are to mitigate risks, create fit for purpose standardised models and improve ROI.

The 2018 instalment of the SIG identified the biggest hurdles facing us on this path and I’m pleased to share with you this summarised report of the on-site discussions and findings, as well as a series of recommendations for how we move forward.

Innovation is going to rely on partnerships with academics, healthcare providers, government officials, technology enablers and patients. We hope that the Automation SIG will continue to be the home for developing these partnerships for years to come.

Laura Rae Event Manager Phacilitate


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CHAPTER ONE WHAT DOES THE CELL AND GENE INDUSTRIAL REVOLUTION LOOK LIKE?

Dr Stephen Ward Chief Operating Officer, Cell and Gene Therapy Catapult

Since being appointed as the first Chief Operating Officer of the Cell and Gene Therapy Catapult in January 2013, Stephen has established the world-class industrialisation capabilities at both the Guy’s Hospital facilities in London, and has designed and built the innovative manufacturing centre in Stevenage. He brings over 20 years of biological medicine research, development, and manufacturing experience to the organisation. Stephen enjoys bringing cutting edge technologies to patients, by developing commercially viable products. Stephen is passionate about securing and growing the cell and gene therapy manufacturing and development supply chain. He is the current Chair of the BIA’s Manufacturing Advisory Committee, actively promoting and supporting UK biomanufacturing at Government as well as grass root level. His first degree was from the University of Birmingham, and his second degree from the Medical School of Southampton University.

OverviewCell and gene therapies continue their rise from ‘clinically promising’ to ‘commercial reality’ with Kymriah, Yescarta and Luxturna grabbing the headlines. With another bumper year of investment in the sector ($7.9 billion YTD in 2018), continuing the trend of year on year rises(1), the pressures on manufacturing, supply chain and clinical interfacing continue to grow. New GMP manufacturing and supply infrastructure, specifically designed for our sector, is now coming into operation; to allow production, testing and release systems to be developed at scale. The step changes required to deliver at a cost-appropriate ‘industrial scale’ are now becoming apparent; with raw and starting material supply chains being pushed more than before, including quality control platforms.

Whilst the Centralised versus Distributed versus Bedside manufacturing debate continues, the common denominator is the requirement to have enclosed, automated, controlled processes delivering a consistent quality target product profile, at a cost that is affordable to health providers. Automated modular systems are already a feature of many commercial pipelines. The available technologies tend to fall within discrete clusters, depending on the therapy type; autologous mostly developed from the blood industry, whilst allogeneic and viral gene therapy from the existing biopharma industry. The current maturity of the industry dictates that flexibility within the process unit operations is required, at least for the short term, which is why modular integration is currently attractive; allowing process parameters to be established and subsequently confirmed over time (see Figure 1).


Without assurity of process, committing to the often-substantial investment needed to provide a fully ‘integrated’ automation solution can be a difficult step for companies. It is highly likely that fully integrated processing shall follow the current phase of modular automation for autologous processing, as systems are already available and are being used more widely, whilst gene editing technologies and challenges in downstream purification and fill and finish for allogeneic processes will provide opportunities for novel automation systems in this area. Whatever the therapy, investment in automation requires a sound business case, based on a detailed COG’s analysis founded in health economic assessments. Overlooked for too long by our sector, is the need to drive quality control into our processes and not rely on testing it in at the end. Batch wastage and long ‘QC pending statuses’ are not viable for our industry. A concerted focus by us all to improve in-process testing is needed, whether at-line or in-line, to increase certainty of batch success. Of course, appropriate processing methods to make adjustments based on these data loops are also required, to maintain the process within the approved operational space. Long processes, such as used for iPSC or ESC derived differentiated cells products, absolutely need these methodologies, to prevent batch rejection disasters. New sensor

technology, linked to proven CQAs e.g. rapid flow-based and digital methodologies, make this area highly impactful and exciting, including rapid release safety tests: the potential for open-innovation in this area is significant and is starting to get traction.

In addition to innovation within the processes themselves, we also need developments in the overarching control and delivery systems that are going to be essential to deliver these products, in an efficient and reliable manner. Supply chains, facility design, data management, QA approaches and product release approaches are all exciting areas for change and investment. Facilities to develop and then try out these new systems to de-risk the future, are an exciting reality across the globe. As we move into a new industrial age, as a sector we need to look more to other industries who have gone through their own ‘industrial revolution’; to benefit from lessons learnt and identify new systems which could transform our own ‘transformational medicine’ industry.

Reference 1: Alliance for Regenerative Medicine Quarterly Data Report (Q2 2018)

Process Automation – Higher productivity & Lower costs

1

Manual

• Established processes• Open process steps• High risk

Modular Automation

• é Reproducibility• é Robustness• é Integration

Bolt on process control

Integrated Automation

• é Containment• é Efficiencies• ê Labour

Integrated process control

Automation step change

• é Throughput• êFootprint• Optimised costs

Predictive process control

Industrialisation

COGs

Fig.1 Process automation - higher productivity and lower costs


CHAPTER TWOMAKING THE BUSINESS CASE FOR AUTOMATION: HOW TOOL PROVIDERS AND MANUFACTURERS DECIDE WHETHER TO INVEST IN AUTOMATION

Dolores Baksh Innovation Leader, Cell & Gene Therapy, GE Healthcare

Dolores Baksh is Innovation Leader of the Cell & Gene Therapy business at GE Healthcare Life Sciences. In this role Dolores works with the various business functions, R&D, product management and commercial teams to address the rapid technological and digital needs of the cell & gene therapy field to drive the development of innovative solutions.

“Great to see cross-sharing from the participants in the sessions at Phacilitate’s Automation SIG, with specific and real-world case studies being shared” Dolores Baksh, Innovation Leader, Cell & Gene Therapy, GE Healthcare

Rodney L. Rietze Director, Strategic Development and Innovation, Novartis Pharmaceutical Corporation

As Director of Strategic Development and Innovation, Dr. Rietze supports the development of novel bioprocesses, analytics and other enabling technologies for next generation cell and gene therapies, as well as the global manufacture of Kymriah™, the first FDA-approved personalized CAR-T cell therapy.

“In the time since Phacilitate’s last Automation Special Interest Group, we have observed the commercial approval of both cell and gene-based therapies. While exciting, these approvals highlight our need to rapidly develop novel technologies and to work together to deliver these life-saving therapies on a global scale.” Rodney L. Rietze, Director, Strategic Development and Innovation, Novartis Pharmaceutical Corporation

Kathie Schneider Product Marketing Manager, Cell & Gene Therapy, GE Healthcare

Kathie Schneider is the Product Marketing Manager in the Cell & Gene Therapy business at GE Healthcare Life Sciences. In this role, Kathie works to understand the manufacturing challenges in cell therapy manufacturing to promote solutions and information that helps move the industry further.

“Taking the time to understand the drivers and points of view between manufacturers and solution providers can increase overall collaboration to help provide innovative solutions for this rapidly evolving industry.” Kathie Schneider, Product Marketing Manager, Cell & Gene Therapy, GE Healthcare

OverviewThe field of cell and gene therapy is in a state of acceleration. One of the key objectives for the field is to deliver cost-effective, scalable and robust processes.

In order to meet this objective, both manufacturers and tool developers (solution providers) will need to justify their “build vs. buy” solutions. Although both parties are dependent on one another to deliver the right solution on time, they are both driven by very different metrics when making the decision to invest in automated solutions.

This chapter explores these priorities in more detail, and focuses on collaboration as a key to unlocking an optimal solution.

Background The cell and gene therapy industry needs technological innovation to keep pace with accelerating drug discovery therapy pipelines. Drug manufacturers in the cell and gene therapy field have (for the most part) started their development work by adapting existing tools and solutions to test and prove their process. However, over time, solution providers have realized that more technologically advanced tools are needed to help manufacturers meet the growing demands of the field.

Over this recent period of development and clinical success, it has become increasingly apparent how important it is for solution providers and manufacturers to interact with one another if they are to advance the delivery of the right tools and technologies and thus progress the field.


The view from solution providersFor tool and solution providers, working closely with the end-user early in the development process is critical if they are to identify their customer’s key requirements and produce a “best in class” automation solution that can be delivered to the market in a timely fashion. As such, solution providers often seek to work in agile ways with manufacturers to deliver solutions that meet their customer’s needs today and in the future.

It is difficult in such a fast-moving field to predict exactly what this ‘future’ looks like. Hence the need to incorporate an agile design philosophy that focuses on delivering that which is required ‘today’ as a minimum but which has the flexibility and capability of add-ons such as hardware/firmware upgrades over time.

Depending on the solution provider, there are key metrics used which will need to be applied to justify investing in building an automation solution. In general, a solution provider will need to deliver on financial metrics such as net present value/payback period and they will need to evaluate whether such investment is within their core R&D competency. Justification of R&D spend over time, time spent on development work, and moreover, their ability to deliver a “best in class” solution to the end user will all form part of this decision.

This decision needs to be supported with a deep understanding of the competitive landscape and IP space, and a critical evaluation of their solutions place in the market. For example – service providers might ask themselves;

• Is this service already available?

• Is the solution going to be a “me-too” product where price justifies incremental functionality?

• Is the product truly transformative?

Ultimately, the value story needs to be one with a solid business and market assessment that can justify the investment.

The view from manufacturersThe time it takes to get regulatory approval and to get to market features heavily in manufacturers’ consideration to build or buy an automation solution.

Manufacturers are prepared to work closely with solution providers to ensure that their requirements are being considered in early technology development and are often willing to beta-test prototypes throughout the development pathway. This partnership can be extremely useful for providing regular feedback on design which can then inform the next iteration of the product.

Depending on the depth of information shared, this might translate to many different types of collaboration agreement that provide beneficial commercial terms such as first market access, preferential pricing and exclusivity periods. The risk/cost sharing contributions on both sides will determine the extent and time duration of this exclusivity.

Manufacturers are also concerned about the security of supply and their reliance on a single supplier for critical technology. However, a comprehensive master supply agreement can be put in place to retire this risk and hold each party accountable for continuity of business. Generally, manufacturers are more in favour of a standard ‘off-the-shelf’ product that can be customised (if necessary) to fit their purpose, rather than an all-in-one custom solution.

Fig.2 The summarised views of solution providers and manufacturers


Recommendations for industrySolution providers and manufacturers are already working together and continue to search for optimal ways of collaborating to accelerate the delivery of next generation solutions. By working together and understanding what drives decisions, timelines and costs, solution providers and manufacturers can ultimately reduce development costs and accelerate the delivery of an automation solution. Data sharing As this is a highly competitive landscape many manufacturers are reluctant to share their data or results in the public domain owing to the threat to intellectual property pursued as part of their drug manufacturing process. Herein lies the conundrum for this field. Drug developers need this information to test their data and validate their workflow and the solution providers need this data too, so that they can validate and refine their solution as they continue through their development process. Both parties must find a balance so that enough data can be shared to understand whether the product meets their respective biological, operational and financial requirements without impacting their company’s position through excessive data exposure and sharing.

One possible solution is through mutually beneficial agreements made between the manufacturer and solution provider around key areas of interest. This would enable a sharing of risk between both groups and if successful, may result in unique rewards such as periods of exclusivity, discounting of devices and/or consumables and/or perhaps shared IP.

Another option could be a risk/cost partnership for sharing resources that could be deployed to each site to help accelerate product development. This solution consists of embedding either the solution provider at the manufacturer, or having someone from the manufacturer’s lab working with the device at the solution provider’s site. While this allows for a greater degree of collaboration, there is still a need to structure an agreement on the use of data generated by each side.

Staying agile Both manufacturers and solution providers agree that it is important to take a collective view, evaluating what is out there to avoid re-inventing the wheel. Both must understand that at times a minimally acceptable solution that meets today’s requirements is more important than waiting for a fully integrated solution that could take years to bring to market. An agile framework that considers the development of a flexible, configurable and modular solution should accommodate any changes in business model and ease new technology integration. This should be complimented with early discussions with key stakeholders to develop a deep understanding of the drivers for ROI for each party. In addition to staying agile, it’s important to prioritize a collaboration structure that considers meeting these ROI metrics in a phased approach.

In the end, for these collaborations to work it goes beyond the product/ solution itself and must be about trust in each other’s ability to develop and evaluate the product.

The key lesson from this chapter…Efficiently enabling and accelerating technological developments to meet the increasing demands of capacity and cost of goods requires collaboration. Every side will have objectives that are unique to them, and the key driver will be having the various types of collaborators, including solution providers and manufacturers, understand each other’s objectives and work together to find solutions that can achieve a better outcome that benefits all.


CHAPTER THREEREVISITING THE ‘WHEN’ OF AUTOMATION WITH PRODUCT DEVELOPMENT AND QUALITY CONTROL IN MIND

Brian Hampson Vice-President, Manufacturing Sciences and Technology, Hitachi Chemical Advanced Therapeutic Solutions (“HCATS”)

Brian has provided over three decades of engineering leadership to drive innovative development and deployment of technologies, devices, systems, and automation for cell-based processes. At HCATS, he provides executive oversight for Manufacturing Development and Innovation & Engineering teams dedicated to solving the challenges of cell therapy manufacturing.

“Automation has been a central focus throughout my career. A constant theme is planning. Answering and re-answering fundamental strategy questions is critical for return on the significant investment involved.” – Brian Hampson, Vice-President, Manufacturing Sciences and Technology, Hitachi Chemical Advanced Therapeutic Solutions (“HCATS”)

Wilfried Dalemans Chief Technical Officer, TiGenix NV

Wilfried is the Chief Technical Officer responsible for the global technical operations, encompassing coordination of product development and life-cycle in R&D and industrialisation, and overseeing the clinical and commercial manufacturing operations of the company. As former VP of Regulatory Affairs he obtained the first central European approval of an ATMP, ChondroCelect, a cell therapy product for cartilage repair.

“Understanding and mastering the challenges of robust manufacturing at a sustainable COGS is critical to the eventual success of commercializing a cell therapy product. At the same time, in the context of funding limitations and stretched budget management as experienced in biotech companies, major investments in automation of the process need to be done at the right time. A good balance between process improvement, regulatory risks, and timely investment will drive the “best time” to implement automation.” Wilfried Dalemans, Chief Technical Officer, TiGenix NV

OverviewAutomation is a solution to be applied, not a problem to be solved, although solutions need to be guided by clear statements of the problems at hand, especially as they themselves can often raise new challenges.

The focus of this chapter and its corresponding session at Phacilitate’s Automation SIG was to compile a roadmap of inputs needed for planning the when, where, why and how of automation solutions within the larger strategic context of the product development journey. The roadmap needed to consider business strategy, regulatory requirements, assurance of product quality and their multitude of potential risks.

The ultimate goal being to guide the big questions around when to automate, how to navigate regulatory hurdles and effectively deploy automation so that we can manufacture commercially viable products with consistently high quality, and a reasonable cost of goods capable of meeting demand (scalable) and can doing so over the life-cycle of the therapy (sustainable).

Outcomes from this session were organised into three areas of strategy;

1. Business strategy (e.g. timelines/ milestones, market projections, funding, exist strategy)

2. Regulatory strategy (e.g. comparability management)

3. Product quality strategy (e.g. process optimization, quality risk management)


Fig.3 A poll of participants was taken at the beginning and end of the session to answer the question “What is the right time to invest in automation?”

• Pre-clinical stage

• Early clinical stage

• Late clinical stage

• Market authorization stage

• Commercialization stage

• “Gen 2” product stage

• After the industry matures further

• After automation technology advances further

• Something else

• Not sure

Part i) Regulatory strategy

The earlier automation is introduced in cell therapy product development, the better positioned cell therapy developers will be to mitigate the resulting regulatory risks. Risk assessment across all the elements for manufacture of the product (process, analytics and information) is a key tool that does not require substantial investment, but is a valuable exercise to perform early in development and then to update periodically as product development progresses.

Identifying where risks to product comparability are highest for introducing automation and then prioritising the mitigation of those risks before substantial clinical data is generated can avoid what has largely been the case so far, late stage or commercial cell therapy processes with limited automation and substantial risk associated with making the changes needed to incorporate automation.

Regulatory strategy also needs to ensure the full range of compliance requirements are addressed, which includes elements such as extractables/ leachables for product contact components of automation, automation process validation, and quality assurance of raw materials.

Part ii) Business strategy

Automation takes time and money. A typical business needs to control timeline and funding risks, while also navigating the progression to achieving goals for clinically and commercially viable manufacturing.

A quality target product profile (QTPP) should be created early as a living document that not only identifies quality attributes of the product, but also key business attributes such as target cost of goods, estimated market demand for the product over its commercial life, and key clinical and commercial milestones. All of which are important in informing the strategy for automation. These attributes may be difficult to determine early on, but it is still more valuable to establish targets that are very likely to change instead of ignoring until a later time.

The typical primary rationale for automation from a business perspective is to address commercialisation needs around cost of goods (COGs) and scalability. Since these elements typically have lower importance at a clinical stage (where there is still significant process and product uncertainty) the tendency has historically been to defer focus on them until there is sufficient clinical data and confidence regarding the commercial prospects for the therapy.

However, an evolutionary step-wise approach that starts with “foundational automation” provides a strategy that balances the competing needs. An example of what this progression could look like is shown below.

Phase 1 Feasibility trial:• Begin to understand the process and define unit

operations

• Appreciate that there is still significant uncertainty about the process so it doesn’t make sense to pursue significant automation yet, but look for approaches that are “automatable” in the future.

• Understand what can you measure, what can you control?

Phase 2 trial:• Explore existing automation solutions for relevant

unit operations

• Begin to implement “plug and play” (off-the-shelf) automation solutions, particularly where product comparability risk is high if automation is deferred (“foundational automation”)


• Pursue automation that mitigates significant risks identified by risk assessment, as well as “low-hanging fruit”

Phase 3 Registration trial:• Typically not the point to consider substantial

changes to manufacturing

• Ensure robust and comprehensive ability to capture data that can support comparability assessment when needed down the road.

Pre-commercialisation:• Pursue automation that does not present product

comparability risk (e.g. electronic batch record/execution system, automated analytics)

• Prepare for scaling and sustainability of automation solutions implemented in registration trials

Post-registration, possibly a “Gen 2” manufacturing capability:• Explore more sophisticated options such

as bespoke solutions with extensive factory integration

Part iii) Product quality

Automation is often a key strategy to control or improve product quality, either as a stand-alone justification or along with business justifications such as COGs and scalability as discussed above. The recommendations from the group on this discussion point were as follows;

• As part of the QTPP, critical quality attributes (CQAs) should be identified at the front end of the clinical development program and include attributes for identity, purity, potency, dosage, and safety. Safety is an overarching requirement and automation that addresses a significant safety risk should certainly be first priority. For example, automation usually is combined with closed processing which can mitigate the risk of microbial contamination of the product which is particularly of value when a fresh product must be administered before final sterility results are available.

• Quality risk assessment (guided by ICH Q9) should be performed early in clinical development and updated periodically to identify key quality risks that can be mitigated by automation, including risks of human error and excessive variability due to manual operations.

• A robust analytical tool box should be established as soon as possible that can be confidentially relied on to generate suitably accurate data necessary for automation decisions. At the same time, data capture

methodology should be established to ensure data can be accessed and analysed effectively as development progresses and the volume and complexity of data grows.

• A rigorous quality management process is of the utmost importance.

It should also be noted that automation being implemented for reasons unrelated to product quality (e.g. reduction of COGs) can nevertheless have a negative impact on quality. While humans are prone to error they can provide exquisite feedback control in a process that can either subtly contribute to quality or which can lead to action being taken before there is an impact to quality, each of which can be difficult to automate.

The team leading automation efforts is often different from the subject matter experts for the underlying process and so it is essential to establish a strong collaboration between the two in order to manage the unintended side effects of automation.

What does this mean for the industry?The industry is beginning to move beyond the “Catch 22” where clinical data is needed before justifying the expense of automation. Once clinical data is available it is often too late, or at least very costly to automate, especially with the regulatory risks which have to be managed in order to demonstrate product comparability. Suitable technologies and automation platforms are becoming more and more available and it is now time for automation to take front and centre in clinical development, driving the planning and implementation of automation earlier and earlier, even before Phase 2.

The key lesson from this chapter… Begin your automation efforts early (ideally in the early clinical stage of product development) but guided by a plan for stepwise progression that manages regulatory, business and quality aspects as well as other risks on the way to commercialization i.e. the ‘Foundational Automation’ approach.

To quote one participant at the Phacilitate Automation SIG

“Automate early, automate often, automate everything”


“At Phacilitate SIG it was a rich and solutions oriented set of discussions concerning the next steps in Cell and Gene Therapy and how might automation play a role. In our goup session it was great to step past the current CAR-T therapies and explore how will automate and manage COI/COC for all type of cell therapies including long term patient follow up for both autologous and allogeneic products” Heidi Hagen, Chief Strategy Officer, Vineti

Overview In cell and gene therapies (especially autologous therapies), the patient is the process, the product, and the treatment. Given the unique supply chain needs of this patient-centered ecosystem and the fact that standards are now just emerging it’s important to look at the major issues affecting supply chain strategy, integration, compliance, and stakeholder management and the active steps that are being taken to create supply chain scale, traceability, visibility, and control. Cell and gene therapy supply chains are the most complex therapy supply chains in the history of medicine to date. Traditionally, mistakes in the supply chain have been an annoyance that will cost time and money to correct. In the scenario of cell therapies like CAR-T in leukemia or lymphoma, an error is the difference between life or death. Part and parcel to the supply chain are the Chain of Identity, Chain of Custody and Chain of Condition - with integrated traceability.

Fig. 4 SIG participants were asked at the beginning of the session ‘Do you feel that standards, best practices and technologies are coming together to address this complex cell therapy supply chain system?’

The key takeaways for this session can be summarised as

i) Integrating existing solutions

ii) Defining critical data needs

iii) A need for standards

CHAPTER FOURSUPPLY CHAIN AUTOMATION AND INTEGRATION

Tamie Joeckel Head of Global Alliance, Vineti

Tamie leads the global alliances effort for Vineti, identifying and managing integration partners for Vineti’s platform. Tamie has a background in both clinical trial logistics and commercialization of specialty biologics having served as the head of sales for PAREXEL’s global clinical supply group and Vice President of Trade for AmerisourceBergen Specialty Group. Prior to Vineti, Tamie was the Senior VP of Client Services for Cryoport where she led teams that supported over 120 global clinical trials in cell and gene therapy.

“These therapies require a never-before-seen, complex ecosystem to support them. The Phacilitate SIG session that Vineti hosted was a great representation of diverse stakeholders from clinical research, providers, manufacturers and service providers. It was interesting from the breakout sessions to hear the continuity in the challenges we need to solve - lack of standards, protecting patient safety, handling & logistics, and capacity/ability to scale.” Tamie Joeckel, Head of Global Alliance, Vineti

Heidi Hagen Chief Strategy Officer, Vineti

Heidi is the Chief Strategy Officer and a Co-founder of Vineti. She is also on the Board of Directors of Vericel and the Chair of the University of Washington Bio-Engineering Department Advisory Committee. Previously, Heidi was the Global COO for SOTIO a.s, the SVP of Operations at Dendreon for ten years responsible for the first active cellular immunotherapy approved in the US, and had multiple drug development roles at Immunex Corporation for ten years.


Part i) Integrating existing solutions

There are existing solutions within each of the supply chain links today which need to be integrated and threaded together to allow for full data transparency and control for all stakeholders. The complexity of integration and management of these different systems should be recognized and addressed with integration solutions.

All stakeholders need to be engaged, especially clinical sites and medical staff. Organ transplants and other allotransplants have been safely managed and administered for decades and these best practices and work flows can be modified and enhanced to manage cell therapies.

We are hearing more frequently that the last 50 meters are out of the control of the cell therapy companies, but is that control really needed? Or is the integration into existing systems, workflow, and data management what needs to be reviewed?

Part ii) Defining critical data needs

Real time monitoring and feedback response will add to the therapy costs. We need to evaluate the level of monitoring and the critical data required depending on the type of product and mode of delivery.

For the current high cost/priced CAR-T products ($500K+), real time monitoring throughout the supply chain is reasonable. However, for the higher-volume and broader-based indications the monitoring will need to be more value-based and data-driven. For example, regenerative cell therapy for spinal defects and discs competes with painkillers on a cost basis; thus only the critical data points should be monitored and linked for a complete feedback loop.

The scientific data required from the chain of condition (environments that the cells encountered from acquisition to patient administration) requires further research and development. In Chain of Condition (COC) monitoring, what temperature factors are truly important for particular cell types and when does an excursion necessitate intervention?

In summary, the cost-to-benefit ratio for deep and invasive monitoring throughout the supply chain versus “good enough” has not been established yet.

Part iii) A need for standards

We need to develop global standards while managing conflicts of interest inherently born from the personalized nature of cell and gene therapy.

Specifically, Chain of Identity (COI) exists from the point that the patient is prescribed a cell product and throughout their lifetime with health records. Patients are mobile, the data is private, and access to health records can be controversial, with different parties having different agendas for the data.

Global standards for managing and accessing this data need to exist for proper therapy management and patient follow up. Conversely, Chain of Custody (COC) is a time-bound record of the tangible product and existing GMP/GCP systems provide the standards that can be integrated under a regulatory authority’s guidance.

COI—the inextricable link of a patient to all cell products made and provided to that patient

COC—a fully auditable record of who touched the product, what they did to the product, when/where the action occurred from cell

acquisition to administration

What does this mean for industry? In this new frontier of medicine, we haven’t treated enough patients to gather data to help with predictability and outcomes. Utilizing technology, whether in patient selection & management, manufacturing, or logistics traceability can only help us gather critical data points that will be valuable in both long term outcomes and predictive analytics.

Cell and gene therapies require a set of standards in traceability and the need to automate the supply chain in a way that is flexible enough to accommodate the wide variety of cell therapies being developed today. The safety of the patients and the adoption of cell therapies depend on the industry’s ability to create these standards to ensure both the safe handling and delivery of individual therapies, but also a lifetime of follow up for those patients that receive the product.

The key lesson from this chapter…It clearly “takes a village” to bring these therapies to market and companies should consider the implementation of technology as early as possible to support the lifecycle complexities. Tracking a few patients on spreadsheets is manageable in very early phase, but more robust technology solutions will ensure complete data capture which can ultimately support outcomes and analytics in the future.


CHAPTER FIVECREATING A ‘RATIONAL SUPPLY’ TO REDUCE MANUFACTURING TIMELINES AND PRODUCT VARIABILITY

Fergus McKenzie CEO, SAKARTA Ltd.

Fergus started the Stem Cell programme at GE Healthcare, and directed the world’s largest (in 2010) automated human embryonic stem cell (hES) production and screening facility. Fergus is currently dedicated to the delivery of a cost-effective automated GMP manufacturing system for the cell therapy industry.

“As clinical success of cell therapies becomes the ‘norm’ rather than the exception, we find ourselves at the point we can work together to improve standardisation, reduce manufacturing costs and deliver cost-effective therapies where everybody wins. Phacilitate’s Automation SIG will play a major role in achieving these goals.” Fergus McKenzie, PhD, CEO, SAKARTA Ltd.

OverviewThis chapter explores the major issues affecting supply chain management and process variability and the active steps that can be taken to reduce variable inputs in an expensive manufacturing system where failure to generate an end product may have more than financial consequences.

Before beginning this chapter’s corresponding session at the Phacilitate Automation SIG 2018, the following question was asked of participants:

“Do you feel you may have to re-invent the wheel, despite the fact that potential solutions to supply chain challenges may exist?”

The general opinion of all present was that this was indeed the case, although at the end of the session we had generated some thoughts and directions that could be taken to alleviate this situation to a certain extent, these fell into the following 3 categories;

i) Ensuring a sustainable and affordable supply of materials (reagents, media, consumables etc) with predefined quality for cell therapy

ii) Identifying and managing sample variables (particularly in autologous systems where donor variability is substantial)

iii) Lowering manufacturing costs through process integration and automation

Part i: Ensuring a sustainable supply of materials with predefined quality

In the case of cell culture media, growth factors and plastic ware, the industry is at the mercy of a relatively small number of suppliers of high quality reagents. If, for example, a problem arises with any reagent then very little can be done to rectify the loss from both the patient and the regenerative medicine company’s point of view. Consumables therefore represent a very high cost to any company engaged in cell therapy.

If we were able to grow most of the stem cells and patient cells in the same media (although this may not be the best media for that cell type) it would reduce the number and variety of expensive medias that have to be produced, thus lowering costs.

How could we move towards a model like this?

• By forming a ‘consortia’ amongst like-minded companies, who can then negotiate superior rates for reagents.

• By changing regulation, so that reagents supplied with a full certificate of conformity should not need re-testing. The original statement from the supplier should be enough for any regulator. It is noted, however, that quality certification introduces a liability issue since producers do not have the profit of therapeutic application, and accordingly they will not accept the risk and liability of qualifying materials.


There are significant lessons that could be learnt from the blood transfusion industry relating to the existence of an infrastructure that allows collection of donor material, cold chain storage, transport to a centralised area and onward distribution following appropriate testing. Though arguably current blood bags and tubing are not actually fit for purpose and our industry should take note when setting up any infrastructure involving ‘closed’ plastic storage bags/ systems. Furthermore, volumes in blood supply is huge – whereas the current number of patients treated in cell therapy is small, so is there enough demand to produce new products?

Standards in supply chain componentsThe whole industry would benefit from a simplistic approach where the absolute minimum number of tests are conducted to deliver approved release criteria.

‘Is the product non-toxic?’ ‘Is the product non-tumorigenic?’

We can ascertain from the years of cell therapy thus far conducted that these products are above all else, safe, and so we do not need to conduct every conceivable test possible. Getting to this level of standardisation will take the concerted efforts of clinicians and regenerative medicine companies, working with the regulators to find common, agreed standards.

Risk contextUnderstanding the context of how much risk is allowed is critical for creating informed standards.

For example – whole genome sequencing is not an appropriate test to derive release criteria as it is not 100% accurate every time and can generate differential data that cannot be analysed. Regulators do not want to ask ‘is a sequence difference important or not?’ until we are absolutely sure of the answer. This is why many of the tests that can be conducted on cell therapy products should be left in the realm of the research lab for the time being.

Material provenanceIt’s accepted that for certain CAR-T cell therapies anything up to 10% of patient samples do not grow appropriately and cannot be turned into product that can be given to the patient. This may be for a number of reasons, most of which are outside the control of the cell therapy company who typically are not using their own trained staff to remove the initial patient sample.

The best recourse here is to design a manufacturing process that can deal with highly variable samples. This is a failing of the process and will require technical progress to deal with difficult samples. When the inability to grow a sample from a patient is a consequence of poor cold chain maintenance or a logistical element, then this can be rectified by a full analysis of the chain of custody.

Question 2: Identifying and managing sample variables

It is accepted that of the two models to deliver a cellular therapy, namely ‘Centralized’ and ‘Decentralized’, the former is very much easier to control whilst the latter opens up the possibility of multiple human errors.

Sources of variability can stem from different donors, doctors, sites and methods despite attempts to engage physicians in training programs and software being implemented to control samples in real time. A commonly held concern for the industry is that it is not always possible to have a distributed clinical network adhere to the clinical protocol needed. Making the challenge about administration and apheresis. The superior strategy would be to remove human intervention as far as possible, developing proprietary administration equipment to reduce errors in cell handling.

It’s difficult to assess how much variability is introduced by inter-operator variability at clinical site administration. It forms another poorly controllable variable that will reduce the effectiveness of the therapy. Although it should be noted that there are several players in the sector who are beginning to offer ‘complete’ solutions, such as Cryport who have just signed deals with two major CAR-T therapy producers to deliver supply chain solutions between clinical and manufacturing sites.

Given that sample variability is difficult to control, we have to ask whether a decision to proceed with product release is driven by the product (the commercial element), or the patient’s condition. There should be acceptance of short-scale, higher-risk release, and when a product is ‘out of the norm’ then the clinician should have final say. A good example of this is whether we should still administer all the products that fail (or have not yet passed) sterility tests (autologous CAR-T). A level of risk is acceptable, but to what degree, especially upon licensing, is debatable.


Question 3: Lowering manufacturing costs through process integration and automation

Lowering manufacturing costs through process integration and automation can be approached in two distinct ways;

i) If you have sufficient money/ resource, then it is preferable to introduce automation as early as possible as it will significantly help your understanding of the overall procedure and will ultimately lead to a regulatory authority approved process.

ii) If you do not have sufficient money/ resource, you will likely have to wait until at least a phase 2b clinical trial where some efficacy of your product has been demonstrated and the possibility of getting a product to market has been somewhat de-risked.

In either case, the first process in place is going to be the ‘worst’ as significant improvements will be made as the product reaches the market and starts generating revenue. Perhaps we have been too focused on developing automated processes where in-line real time measurement is evident. Other than a small number of key parameters ‘at-line’ measurement will likely be sufficient and result in a cheaper overall manufacturing process.

There is a common view that increased and improved automation allied with technical progress from the bench will reduce costs for cell therapies, but this is not going to happen overnight and the cost reduction may not be significant.

What does this mean for the industry?Only companies who have major resources and ‘deep pockets’ will be able to afford to work-out the supply chain problems on their own. For everyone else, the easiest way to shorten the path to the clinic and reduce costs will be to form loose associations or collaborations between several companies.

At the same time, all efforts should be made to work with the regulatory authorities, who see the same challenges with each company they work with yet cannot share solutions for reasons of confidentiality.

At present, the ability to progress a potential cell therapy to the clinic is a risk management process. Each company is doing its best to minimise that risk, but perhaps the final decision should be left in the hands of the clinician. For example, sterility testing can often take up to two weeks but in many cases a patient will not have two weeks remaining. The decision to proceed with a treatment that has not

been shown to be free of adventitious agents may still be preferable to the patient dying because the test took too long to be received. A clinician may take the view that it’s easier to cure an infection, than a late stage cancer.

As an industry there are several potential items that could be addressed to shorten the path to the clinic. These include;

1. Standardisation of media types and consumables so that most cell therapies are grown in the same media, significantly reducing the low volumes and high costs associated with bespoke solutions

2. A review of regulations so that a certified chemical sold by a manufacturer does not require further certification by the purchaser

3. Simplified processes where possible – avoiding making a process more complex because there is added functionality. Knowing and trusting the difference between ‘best’ and ‘good enough’

4. Faster sterility testing

5. Applying a risk management context, if something is out of specification then who should decide whether it is administered to the patient?

6. Automate - where cost-effective OR where you can remove the capacity of humans to change the process

7. Make the supply chain more robust with real-time supply chain/ logistic management

8. Communicate! Get early advice from academics and companies and integrate it.

The key lesson from this chapter…In order for current and future therapies to be delivered to a large number of patients, we need to massively increase the infrastructure available. This will be the rate limiting step. It cannot be left to each company wishing to bring a new regenerative medicine treatment to market to build the required infrastructure; this has to be done through partnership with healthcare providers, government agencies and health insurance providers.


CHAPTER SIX AUTOMATING BIOANALYTICS

Damian Marshall Director, New and Enabling Technologies, Cell and Gene Therapy Catapult

Damian Marshall is the director of New and Enabling Technologies at the Cell and Gene Therapy Catapult and has almost 20 years of industrial experience gained working for SME’s and large companies. He is responsible for providing vision, expertise and leadership to a multidisciplinary team of scientists who work closely with therapy developers, technology organisation and standardisation bodies. Together they are addressing some of the fundamental challenges in the field, helping develop smarter, cheaper and more controllable processes that will support the transition to therapy manufacture at an industrial scale.

Nicolas Markadieu Analytical Development Expert, MaSTherCell

Nicolas holds a Master in Chemistry and a PhD in Biomedical Sciences. After a postdoc in The Netherlands and also in United States, he recently joined MaSTherCell, QC Department R&D where he is involved in a research project on transduction of liver cells into pancreatic beta-like cells.

“Automation is becoming the spearhead of the biotechnology companies. I am looking forward to having stimulating discussions on how to phacilitate automation.” Nicolas Markadieu Analytical Development Expert, MaSTherCell

OverviewAutomation of in-process analytics and final product release testing could revolutionise the cell therapy industry, allowing the development of efficient, well controlled and robust manufacturing processes that can accommodate the complexity associated with living cell products. However, there are currently very few analytical technologies that are routinely used to provide in-process data and final product release testing is often quite simple. So how can we change this? This chapter focuses of the benefits of

assay automation, current and future automation requirement within the field and strategies for integrating automated analytics into cell and gene therapy manufacturing processes.

Where will the automation of analytics have the biggest impact? Establishing an automation roadmap can be a significant challenge. However, in discussions at Phacilitate’s Automation SIG it was felt that during early stage clinical development the biggest benefits would be realised through a step-change in sterile sampling and assay automation which would allow for controlled, traceable and rapid processing of samples at line, close to the process stream. This could be combined with automated data analysis to allow results to be rapidly generated and improve process decision-making.

At-line assay automation would also allow sufficient flexibility to screen larger numbers of cell quality markers which can then be refined as clinical data is generated. An advantage of assay automation is that it could offer near term benefits, as commercial systems are available for automated sampling, robotic liquid handling and data processing. The application of a robotic system could also allow assay miniaturisation reducing sample volumes and assay costs. This could be of particular benefit for products manufactured in low physical volumes.

Where will the automation of analytics have the biggest impact? In the longer term, in-line analytics would be beneficial particularly if they could provide real time data for critical parameters and allow tighter control of the manufacturing process. This may prove complex and raise a number of challenges, such as;

• A lack of clarity on what to measure

• A preference for in-line sensors to be cheap and single use

• Complexity around sensor calibration

• Making sensors flexible enough to be used in different production platforms

These challenges are not insurmountable but would require closer collaboration between technology developers and therapy producers.

Factors to be considered when designing an in-process control strategy;


Timeframe

How long it will take to integrate an automated technology into the production process? Does it provide significant advantages over manual analytical approaches?

Process risk

Does the automated analytical technology decrease manual workload without increasing process risks?

Sampling

How much sample is required for analysis? Does the sampling approach increase the risk of contamination?

Cost

Does an automated analytical approach offer a sufficient return on investment compared to manual analysis?

Complexity

How easy will it be to integrate automated technologies into the manufacturing process? How simple are the technologies to use and do they provide clear unambiguous data that can facilitate decision making?

Robustness

Do automated assays or sensor technologies perform within acceptable levels of measurement variability when performed at different sites? On different equipment? When analysed by different operators?

Operating range

Do automated assays and sensor technologies provide sufficient dynamic range and are they amenable to validation?

What would it take to automate analytics and integrate them into a manufacturing process?There is an increasing demand for analytical systems which can provide an understanding of cell quality at key (and preferably all) stages of the manufacturing process. This is not dissimilar to the manufacturing requirements in the biopharmaceutical field where concepts such as process analytical technologies (PAT) are starting to be adopted. PAT is a framework launched by the FDA in 2004 which aims to measure, analyse, monitor and, ultimately, control all important attributes of a bioprocess to maintain or improve product quality.

So how do cell therapy developers take advantage of PAT? One approach is to translate existing technologies. However, most biosensors are designed for large volume stirred tank bioreactors, a platform not widely used by our industry. Instead its more likely that implementing PAT to monitor, and control cell therapy bioprocesses will require the development of novel technologies that are flexible enough to work with the wide range of production platforms currently used. This presents an opportunity to develop common interface standards for cell therapy bioprocessing equipment to allow in-process analytics to be modular and adaptable as processes change. Having modular analytical technologies would also allow the flexibility to remove measurements from the process stream if they are no longer required.

Prior to considering the use of PAT it is essential to define what parameters or cell quality markers must be measured. This can be challenging as they are often poorly defined. However, this could be overcome through detailed product characterisation using ‘omics’ technologies and Design of Experiment approaches for process optimisation to gain a holistic understanding of product biology and processing effects.

Recommendations for creating more collaborative approachesTo have a real impact for the field a more joined up approach is needed. Some recommendations for how this might happen are as follows;

Workshops

There is a need to come together as a community to identify common measurements (beyond cell counts and viability) and opportunities for integrating analytics. This could be achieved through a series of workshops at key international events.

Data sharing

Opportunities for organisations to share certain types of data in a pre-competitive environment could be used to accelerate the development of sensor technologies for PAT.

Big data and AI

Greater cooperation within the community (particularly around data sharing) may present opportunities for implementing big data analytics and machine learning. Most organisations don’t generate sufficient data individually to exploit the opportunities in the AI space but through cooperation, concepts such as ‘digital twins’ could be used to develop new more efficient manufacturing platforms.


Cross-organisation collaboration

Closer interactions are needed between therapy producers and technology developers to stimulate innovation and to promote the development of new sensor technologies that can be integrated in cell therapy production platforms.

Is there an industry pull for real time release testing?Real time release testing is a framework to ensure the quality, safety and efficacy of the final drug product based on data generated during the process. There has been a lot of interest in this area over the past few years, particularly in opportunities for implementing rapid microbial tests to confirm product sterility.

The general opinion held by those at the Phacilitate Automation SIG was that rapid sterility tests could be a game changer for product release. For short shelf life products, rapid sterility tests would allow an increased assurance of product safety compared to compendial tests which can take up to 14 days to perform. For cryopreserved products, rapid release tests would reduce storage times and overall cost of goods. PCR based methods would be the most attractive in the short-term for rapid sterility testing as the analytical technologies to perform the assays are well established within QC laboratories.

In the longer term, other technologies are showing promise including the use of dielectrophoresis arrays for microbial capture, and the luciferase based assays used in the food industry. It should be emphasised that the key to the success of rapid release tests, as always, is the ability to validate them within a GMP environment.

What does this mean for the industryOne of the barriers to integrating analytics that was discussed at Phacilitate’s Automation SIG is the inability of the equipment to ‘talk to one another’. Currently, most analytical equipment is used for monoparametric analysis and produces novel data file formats that cannot be readily combined with

other data sources. Having common standards for data formats would support innovation in the development of a processing platform capable of producing data lakes to support advanced multi-parametric analysis. The ability to control, store and access data from multiple equipment formats could also be an enabler for more big-data applications within the field.

More focus is also required on the electronic systems used during product manufacture. Some analytical equipment does not conform to industry guidance for computerised systems used in a GMP regulated environment (21CFR-part 11 in the USA, Eudralex volume 4 annex 11 in the EU). This could be a barrier to data harvesting and more complex product characterisation and should be an area for closer collaboration within the industry and with equipment providers.

One further driver to consider when implementing the next wave of bioanalytical technologies is development of standards. Integrating analytics into a process will require both documentary standards and reference materials. Documented standards will help create a common framework for innovation by defining common vocabularies, establishing essential characteristics of a product and identifying best practices. Reference materials will be an essential enabler of integrated analytics, allowing sensor calibration and validation within a GMP environment.

The key lesson from this chapter…Automation of bioanalytics could offer significant impact for the cell and gene therapy industry allowing the development of adaptive manufacturing strategies that will improve product consistency and quality. Achieving this will require closer collaboration between therapy producers, technology developers, industry standardisation bodies (such as ISO) and reference material producers (such as NIST, ERM, or NIBSC) to accelerate innovation and embed automation into the wide range of systems used for therapy production.


CHAPTER SEVENHOW DO I BEGIN TO APPROACH AUTOMATION, ESPECIALLY WHERE AN ‘EXACT FIT’ TOOL DOESN’T CURRENTLY EXIST?

Behnam Ahmadian Baghbaderani Global Head of Process Development, Emerging Technologies, Lonza

Dr. Baghbaderani is the global head of Process Development, Emerging Technologies at Lonza. He has over 14 years of experience in stem cells engineering, bioprocessing, and cell and gene therapy (C&GT) field. Dr. Baghbaderani holds a PhD degree in Biomedical Engineering from the University of Calgary (Calgary, Canada), where he developed bioreactor protocols for large-scale expansion of human neural stem cells for clinical applications. He completed nearly three years of postdoctoral program including a two-year postdoctoral fellowship at the National Institutes of Health (NIH) / National Institute of Neurological Disorders and Stroke (NINDS). His postdoctoral research at the NIH focused on generation of human induced pluripotent stem cells, bioprocessing of both human embryonic stem cells and human iPSCs and controlled differentiation into neuronal lineage. Since joining Lonza in 2011, he has been working on developing new technologies and manufacturing processes around human pluripotent stem cells. Dr. Baghbaderani then led the cell therapy development department (including process development and bioassay services), focusing on the development of cGMP compliant processes and cell characterization assays for different cell therapy applications. As the global head of process development, Dr. Baghbaderani is currently leading the development activities for viral vector and C&GT applications across Lonza network.

“Implementing automated, scalable, closed system is critical for the development of commercially viable, cGMP compliant manufacturing process. This may be achieved through a carefully planned, phase appropriate process development strategy.” Behnam Ahmadian Baghbaderani, Global Head of Process Development, Emerging Technologies, Lonza

Overview The focus of this chapter is on current approaches for automation in view of the challenges surrounding cell and gene therapy manufacturing as well as limitations around the available tools and technologies.

Manufacturing challenges can exist in quality, quantity and efficiency and often are comprised of multiple, open, manual 2D unit operations. Therefore, it can be agreed that there is a strong need for establishing an automated, controlled and scalable process – the questions lie in how to begin this process, when to begin this process and what limitations exist that need to be overcome in order to succeed.

Part i) How do we begin automation?

A three step process for evaluating and planning a new automated process, or for modifying an existing open, manual process, into an automated one.

Step 1: Look into the end goals concerning dose, indication and pain points identified through risk assessment processes.

Step 2: Evaluate existing technologies and the possibilities of modifications, or custom-building technologies.

Step 3: Road mapping and characterising the process prior to automation is critical

Part ii) When is the right time to begin automation?

Automation should be phase appropriate, and it may not make sense to start automation at the early clinical phase, partly because the main focus for these early phase programs is to produce the GMP grade products and to start the clinical trials as soon as possible.

Considering the challenges with existing automation technologies and time constraints, time to the clinic is often key and it may be costly to spend time on the development of a fully automated, closed manufacturing process.


Instead, the development of the manufacturing process should focus on establishing robust and reproducible unit operations along with significant process and final product characterisation at early phase clinical trials. The process development should then continue in parallel with the ongoing clinical trials to develop an automated, closed system that can be used and examined for the late stage clinical trial (Phase II and Phase III).

While a modular approach can be considered in replacing the manual, open unit operations with carefully evaluated and characterised automated, closed systems, arguably an end-to-end approach for automation can be more feasible for the Phase III manufacturing processes.

Obviously, the decision for implementation of automation, particularly the approach taken for the automation would be a business decision that factors in the size of the corporation, existing technologies and technical limitations including type and number of unit operations involved in the manufacturing process, analytical methods and the result of early phase clinical trials.

Part iii) What are the technological limitations to automation?

For allogeneic applications, the solutions for establishing an automated, large-scale, closed system are more available and can be implemented into the process even at early stage clinical phases. This is particularly true considering the bioreactor systems already established for manufacturing mammalian cells and other biological products over the last couple of decades, and existing bioengineering knowledge in adapting these bioreactor systems for cell and gene therapy applications. Of course, modification of these bioreactor systems could be challenging considering the level of complexity of cell and gene therapy products, which would require monitoring and evaluating a wide range of cellular characterisation and process parameters.

For autologous applications e.g. chimeric antigen receptor (CAR) T cells for cancer therapy, there are several challenges that need to be considered in the implementation of an automation and scale-out strategy. Some of these challenges include limitations with starting materials, type and complexity of the unit operations (e.g. non-viral transfection system, potential differentiation step), regulatory guidelines, sampling plan, analytical methods, downstream processing technologies and final product format (fresh vs. cryopreserved). In order to address these challenges, it is important to perform a comprehensive gap assessment to identify the critical gaps and respective solutions that could lead to a more robust and reproducible manufacturing process.

What does this mean for the industryIt’s widely accepted that automation is critical for the development of a reliable cGMP manufacturing process. It’s vital for addressing concerns about quality (e.g. by reducing number of deviations), quantity (e.g. by improving process yield and scalability) and efficiency (e.g. by eliminating/ reducing the number of labor intensive processes associated with large and high cost manufacturing footprints).

While having a good understanding of the technological challenges, it’s critical to perform a gap assessment to identify the critical process challenges that need to be addressed. This could be done via implementing appropriate in-process controls and monitoring technologies to ensure the process parameters are not significantly changing and impacting the final product profile.

The key lesson from this chapter…Establishing an automated process should be associated with carefully planned in-process control and final product testing to verify that the end product profile is comparable to the expected cell and gene therapy product quality attributes


CHAPTER EIGHT ENSURING BIOPROCESS FLEXIBILITY: HOW TO CHOOSE BETWEEN MODULE OR SUB- MODULE SOLUTIONS

Geoff Ball Manager, Cell Therapy, Invetech

Geoff is a manager in the Cell Therapy Group at Invetech, working with clients to develop industrialised process solutions that dramatically reduce the cost, and increase the safety of manufacturing autologous and allogeneic therapies

“At present cell therapy manufacture is a strange hybrid between highly sophisticated science and cottage industry. It takes several highly skilled individuals to make a therapy for a single person, whereas to meet the demand and to be viable one individual needs to simultaneously produce “doses” for many people. As I see it; this is the primary purpose of mechanisation and automation” Geoff Ball, Manager, Cell Therapy, Invetech

Chapter overview This chapter and its corresponding session at Phacilitate’s Automation SIG sought to articulate a typical process development progression, from fully flexible to fully constrained. Different dimensions of flexibility such as process operation mechanism, chemistry, process parameters, volume/scale, sampling/ bio-analytics and the ideal equipment modularisation to support it are explored and mapped against evolving constraints on the process: regulatory, COGs, QTPP.

This can be split into three core themes;

i) What do we mean by flexibility? How do we define different dimensions of flexibility?

ii) Why do we need flexibility? When do we need it? How can we map optimum flexibility against timing?

iii) Identifying the ideal modules/ sub-modules across the map

Defining process flexibility We explored the idea that there are different aspects of dimensions in a process that we may wish to change or optimise as process development progresses. The following 10 were selected, but without doubt there are other aspects of the process that may need to be changed;

1. Analytical reagents - meaning the reagents used in the QC lab for IPC and QC assays

2. Operator interventions / touches - e.g. early in process development you may want opportunities for operator interventions based on their observations of cell condition

3. Data being captured - early in PD you may prefer a large number of samples and assays to better understand the product, later you may reduce the QC assays to the critical few but increase data capture from sensors for statistical analysis

4. Cell manipulation methods - the core cell process, for example transduction method, or growth factors, or expansion method.

5. Equipment unit ops platforms - the equipment or method for cell washing, media exchange, formulation etc.

6. Starting material - fresh or frozen, leukapheresis, peripheral blood, bone marrow etc.

7. Chemistry (media, reagents, buffers) - includes both selected reagents and also vendor selection and supply chain

8. Bioanalytics - the method chosen for performing key measures of cell biology, typically defined as Critical Quality Attributes in a QTPP

9. Process parameters - flow rates, temperatures, expansion duration, cell concentrations, media exchange volumes, etc.

10. Volumetric scale (dose) - in early stages patient material may be split into small portions for research, at clinical stages a range of doses (cell count) and volumes may be tested.

We found that the transitions from fully flexible to fully fixed progressed at a somewhat different rate for the aspects of the process we had defined as pictured in Fig.5.


Defining typical process development stagesIt is well understood that the degree of flexibility available to process developers changes as drug development progresses to clinical trials and marketing approval. In other words, the consequences of making a change become more significant in terms of both cost and time delays. The group defined the consecutive progression can be found on the x-axis of the figures in this chapter.

Fig.5 Mapping the transitions of flexibility for different dimensions. From light (least costly changes) to dark (most costly changes).

Fig.6 Equipment platform modularity overlays – Manual, lab devices and open fluid transfers in class A hood.


Recognising the transitions of flexibility for different dimensions On exploring the aspects of the process, we recognised that some aspects can remain flexible for longer than others. This is represented in Fig.5, which represents the transition to increasingly costly changes by using darker shading. Note that this was just the view of the team at Phacilitate’s SIG, but it may be possible to quantify this information further by referencing the EU “Guidelines on the details of the various categories of variations”…

How does the optimum extent of modularisation change as process development progresses? For the purposes of this chapter we agreed on the following classifications of modularisation

• Manual, lab devices, open fluid transfers in Class A hood

• Independent unit operation modules automated (eg cell selection, bioreactor)

• Integrated modules, with single manufacturing execution system ideally 1 machine

The benefits for each of these classifications, and their relative location on the process development timelines were then mapped.

Fig.7 Equipment platform modularity overlays – Independent Unit Operations


What does this mean for the industry?We’re aware that the proposition described by the modularity overlay charts above are not so much based on practical experience, but more on an envisioned future.

Nevertheless, the preferred future certainly includes independent unit operation modules that provide reliable, repeatable operations and flexibility in unit choice and parameters. Better still if these modules can later be integrated. At present there are very few examples of modules that provide robust unit operations.

In general, the bioreactors and cell expansion devices are reasonably robust, and the emergence of a number of new options is both welcomed and important. Cell selection techniques are less well established. Most of these methods and modules are subject to the common compromise between purity and recovery. Others are uncomfortably expensive.

Likewise, transduction methods are either unavailable at patient scale (such as electroporation), or unsustainably expensive (vector supply). Other developments are at early stage development and eagerly anticipated.

Furthermore, it is often the case when a cell therapy developer selects automated unit operations they are often faced with performing fluid transfers between modules using open transfers under a hood. Interfacing modules, fluidic connectivity and data connectivity are urgently required.

The key lesson from this chapter…The industry is in urgent need of a range of unit modules for performing unit operations, that have stable and proven performance.

Secondly, standards of interconnectivity are required between these modules for both fluidics, but also data transfer and control supervision.

Fig.8 Equipment platform modularity overlays – Fully integrated (single machine)


CHAPTER NINE FUTURE SOLUTION DEVELOPMENT – DO WE INTEGRATE OR OPTIMISE FIRST?

Mark Dudley Senior Vice President, Bioprocessing, Adaptimmune

Dr. Mark Dudley is a Senior Vice President at Adaptimmune Therapeutics, a leader in genetically modified T cell therapies for solid cancers, where he is responsible for the development of manufacturing science and technology. Dr. Dudley has been a pioneer in the field of immunotherapy manufacturing, and has developed and implemented innovative early process design with accompanying analytics for multiple therapies. Previously, as Director of New Cell Products in the Cell and Gene Therapies division of Novartis Pharmaceutical Corp, Dr Dudley was responsible for establishing scalable, GMP-compliant production strategies and facilitating globalization of CAR-T products and platforms. As Director of the Cell Manufacturing Facility at the Surgery Branch of the National Cancer Institute, NIH, in Bethesda, MD, Dr Dudley investigated tumor rejection tumor rejection antigens, T cell specificity and function, and methods for the generation and administration to patients of T cell therapies. His work has resulted in more than 100 peer-reviewed publications, and he is co-author on numerous seminal papers including early tumor-infiltrating lymphocytes studies demonstrating that adoptive T-cell transfer has tumor eradicating potential. Dr. Dudley earned a Ph.D. in Biological Sciences at Stanford University, and had post-doctoral fellowships at The University of Pennsylvania in Philadelphia, PA and at the Jackson Laboratory in Bar Harbor, ME.

Faraz Siddiqui Director of Tech Transfers and Process Excellence, Product Sciences, Kite pharma

Dr. Mark Dudley is a Senior Vice President at Adaptimmune Therapeutics, a leader in genetically modified T cell therapies for solid cancers, where he is responsible for the development of manufacturing science and technology. Dr. Dudley has been a pioneer in the field

Overview: Manufacturing automation strategy may change as a cell and gene therapy product progresses through its life cycle. An “optimise first” approach values process flexibility and rapid implementation, and so automates individual unit operations. As manufacturing evolves from supplying exploratory trials toward commercial market distribution, fully “integrated” automation solutions have advantages and offer a fixed end-to-end, no-touch manufacturing solution.

This chapter explores the main decisions and drivers in the transition from an “optimise first” strategy to an “integrated” strategy for manufacturing automation for a commercial cell and gene therapy product.


Fig.9 Participants were asked ‘What is required for an integrated automated cell manufacturing system?’ They defined the key requirement for the transition and ranked their importance. Both positive and negative trends emerged, defining high risk and low risk operations during the transition to implement integrated solutions. A full breakdown of results can be viewed in Fig.10

NB: * Manufacturing process understanding can compensate ** Situation dependant *** Situation dependant **** Traceability may supersede CO


The future state of automationWhen exploring a future state in which automation engineers consider whether to develop and optimise each unit operation individually or whether to integrate the entire manufacturing process early in the product life cycle, it’s important to acknowledge that this theoretical discussion would depend most importantly on the attributes of the individual product and its manufacturing process. Specifically, a clear articulation of goals for automating, optimising and integrating process steps is necessary for a successful outcome. For the purposes of this chapter, “automation” is defined as the mechanisation of a process which is currently undertaken by a human,

and “integration” is defined as the combination of multiple processes that are already automated into a single unit process.

In conversation at Phacilitate’s Automation SIG, there were several examples shared where automation or integration activities were not effective. In one case, an automated operation was ultimately less reliable than the original human process and was not implemented.

In another case where two automated processes were combined, the integration project timeline was delayed compared to the product launch timeline, leading to its lack of integration in the product manufacturing process.

Fig.10 Full breakdown of poll results


These examples emphasised that the goals for process optimisation or for automation integration need to be clear prior to project initiation to ensure success. These goals were seen to include not only technical optimisation (e.g. increased cell yield or potency), but also multiple other activities such as quality (e.g. fewer open steps), capacity (e.g. higher throughput within a facility) or lower cost of goods.

Based on this discussion, the group identified multiple attributes associated with commercial manufacturing readiness (Fig.11).

Fig.11 Attributes associated with commercial manufacturing readiness and their importance

Each of these was discussed in the context of its importance in the design of a “no touch” integrated automated cell and gene therapy manufacturing system. There was a diversity of opinions on many of the attributes, and several different visions for the optimal evolution of an automated manufacturing system from early clinical supply to a robust, high-throughput system with low cost of goods. Participants were asked to vote on each attribute and decide whether they were must have, nice to have or not needed. Three attributes were highly desirable, with 69-85% must have and 92-100% nice to have or must have. These attributes are:

• Stable unit operations and unit operations simplification

• Chain of custody and identity

• Electronic data capture

Stable unit operations Stable unit operations and unit operations simplification means that each unit operation of the manufacturing process is sufficiently robust that it performs as expected on the full range of starting material that it will encounter. This also assures that the output from a unit operation will be within expected ranges and tolerances and will be suitable for initiating the next processing step.

Chain of custody and identity Chain of custody and identity might not be considered part of the automated solution themselves but would need to be sufficiently robust to support manufacturing for a centralised automated manufacturing operation. It was noted that if the integrated manufacturing solution were distributed there might be no need for a chain of custody and identity. In the case of a distributed integrated automated manufacturing model, other challenges would need to be solved such as quality assurance and compliance, and QP release.

Fig 12. Chain of custody and identity

Electronic data capture There was a consensus that electronic data capture was extremely important, though 31% of participants thought this was not required, but only nice to have.

Fig.13 Electronic data capture


What does this mean for the industryTogether, the three elements above constitute a minimum amount of process development, product understanding and digital data sophistication needed to de-risk the decision for a fully integrated automation solution.

No participants in the discussion considered a locked manufacturing process to be a requirement for an integrated automation solution. The regulatory equivalence (comparability for implementation) and the new product pipeline (for ease of implementation) attributes were also not seen as critical by the large majority. The low priority seen in this group of attributes reflects that the participants assigned a low risk to the regulatory challenges for implementing integrated automated solutions into manufacturing operations.

An advanced state of process knowledge and understanding would be required for any integrated automation solution and would be a key component of successful comparability studies for implanting manufacturing process changes by establishing automated systems.

Five process attributes were considered by the majority of participants (54-69%) as nice to have, with a sizeable minority considering them as must have.

These were;

1. Manufacturing execution system - supports raw materials and supplies inventory management

2. Predictive control models - used for enhancing manufacturing scheduling and performance and integrating with market demand, facilities readiness, and other business drivers.

3. Autopilot that handles variable starting material - meaning that an integrated automation system will need capacity to make complex decisions based on input from in-process analytics, as well as pre-programmed databases of experience.

4. Facilities fit and flexibility for automation – capturing the challenge of implementing new automation equipment and processes into vestigial facilities

5. Product release assays – whether an integrated automation system would need to include all product release assays on-board.

The key lesson from this chapter…The consensus that all of these important process attributes are not essential to an integrated automation system reflects the multiple visions for an integrated solution and the varied processes that might be automated.


CHAPTER TENDECENTRALIZED MANUFACTURING – WHAT DO THE NEXT 5-10 YEARS HOLD?

Hermann Bohnenkamp VP Business Development, APAC, Miltenyi Biotec

Hermann Bohnenkamp, PhD is VP Business Development for APAC at Miltenyi Biotec. In this role, Hermann works with various business functions and the APAC commercial teams to address the rapid development in the cell and gene therapy field. Joining Miltenyi Biotec in 2009, he was actively involved in the discussion of Advanced Therapy Medicinal Products (ATMP) and raw materials with the European Directorate for the Quality of Medicines (EDQM). He supported investigator initiated clinical trials (IIT), including CAR-T and Treg cell manufacturing in the US and EU, such as The ONE Study or the COST Action A FACTT.

Claudia Rössig Director, Pediatric Hematology and Oncology, University Hospital Münster

Prof Claudia Rössig is Director of the Pediatric Hematology and Oncology Clinic of the University Hospital Münster. Her scientific emphasis is the development of cell based immunotherapy of malignant pediatric diseases. Besides various awarded grants of the German Research Foundation (DFG), Deutsche Krebshilfe, Deutsche Kinderkrebsstiftung, Cancer Research UK, Wellcome Trust and Karl Landsteiner Foundation, she was awarded several prices including the SIOP Price of the International Society of Paediatric Oncology in Brisbane 2001 and the young talent award of the University of Münster in 2004.

“Decentralized cell manufacturing can allow academic researchers to establish the benefit of CAR T cells within investigator-initiated multimodal therapies. Academic manufacturing centers need closed-system and automation technologies to comply with the highest quality standards for cell products.” Claudia Rössig, Director, Pediatric Hematology and Oncology, University Hospital Münster

Robert Deans CTO, BlueRock Therapeutics

Dr Deans is Chief Technology Officer at BlueRock Therapeutics, a biotechnology company creating innovative cell therapeutics by harnessing gene editing tools and pluripotent stem cell biology. Prior to BlueRock, he was CSO at Rubius Therapeutics, a red cell therapeutics platform company. Dr Deans was previously EVP at Athersys, Inc, an adult stem cell therapeutics company now in late stage clinical development, and prior to that VP of Research at Osiris, Inc, developing the Prochymal™ MSC based product line. Dr Deans was also experienced in hematopoietic stem cell isolation and gene therapy while Director at the Immunotherapy Division of Baxter Healthcare. Dr. Deans has also contributed to numerous Regulatory and industry commercialization workshops and societies.

“The enthusiasm to implement automation in our bioprocessing and bioanalytics work streams reflects a sea change of innovation, where the combination with machine learning and artificial intelligence will build robust platforms for early translational success.” Robert Deans, CTO, BlueRock Therapeutics

Overview With two chimeric antigen receptor (CAR) T cell products approved in the US and awaiting approval in the EU, it became clear that one of the clinical hallmarks is a long term durable response, mediated by long-term persistence of these autologous cell products. However, these cell-based and individualized drugs are very complex and need efficient control mechanisms to ensure consistent quality and economy of scale in inventory, materials and personnel.


Industry therefore favours cell therapeutics as a biologic which are used without patient matching requirements. These allogeneic cell products match biologics in product flow and are amenable to reduced cost of goods (COGs) due to scaled manufacturing. Whether such approaches will clinically work with similar efficiencies and long-term durable responses, will be seen within clinical trials.

Part i) What do we mean be ‘decentralised manufacturing’ anyway?

Decentralized manufacturing comes in different grades, from regional approaches such as one manufacturing center per continent, to local, or point of care manufacturing in every hospital.

The industry lens Point of care manufacturing has traditionally been discounted by industry as concerns arise around consistent quality, oversight and inherent regulatory pushback. However, a less efficient economy of scale in inventory, materials and personnel is challenged by new approaches using a fully automated system which demonstrate a general effect on COGs also in centralised approaches.

While CAR-T cell therapies have solved operational capacity hurdles and are moving to bedside delivery, reimbursement will further incentivise decentralised manufacturing by health providers. Regulators are also open to new approaches and to actively discussing which control mechanisms need to be implemented. There has been a “see change” behind how to implement this for CAR-T and an infrastructure is therefore being built within tertiary hospitals which can support personalized medicine, defined as manufacturing on a per patient basis (autologous and allogeneic inclusive).

The academic lens The first allogeneic stem cell transplant was performed in 1965, and this was also the start of decentralised academic cell manufacturing. The impact that it has today is the result of continuous translational research, driven by the academic hematology and transfusion medicine community. Today, more and more complex individualised cell products are generated from patients and donors in academic hospitals. Population-based, nationwide, randomised clinical trials are conducted with every single child with leukemia placed within an individual treatment arm.

Different from stem cell transplantation, CAR-T cell manufacturing following a pharmaceutical model is a black box not transparent to clinicians. In recent trials, some of the patients enrolled never obtained the product, due to manufacturing issues, or they died before receiving it. The investigator’s job during the black box process is to keep the patient alive, often under restrictions dictated by the study protocol prohibiting some of the most effective bridging therapies, and without knowing the exact time to be bridged.

The academic preference is to manufacture CAR-T cells in the same way as other cell products, by in-house manufacturing following uniform standard operation procedures, leaving the entire process in the hands of the investigator. The community is fully aware that the complexity of manufacturing of complex cell products exceeds the standards of community hospitals, but academic (tertiary) hospitals with, for example, JACIE accreditation would be able to manufacture therapies such as CAR-T cells.

Part ii) Do we think decentralised manufacturing is really a necessity for the future?

Are full-process, automated, portable, clean rooms the future of cell therapy manufacturing or should we look to design closed, single-use systems to take processes out of the clean room and fully enable decentralised manufacture?

Platform manufacturing systems automating defined unit operations in an “all-in-one” type device without losing flexibility to adapt unique processes allow for new GMP manufacturing concepts. Concepts such as centralised or regionalised “manufacturing ballrooms” with multiple devices running in parallel processes are an imaginable option. In such ballrooms, with a universal CAR manufacturing license, cell products from different patients and with different CAR constructs may be manufactured.

Such a concept may be applied as a model for decentralised manufacturing of CAR-T cells. Blueprints of the manufacturing process including SOPs, manufacturing procedures and validation protocols need to be generated and trial specific training plans designed. Even today, this has been demonstrated by platforms, such as the CliniMACS Prodigy and MACSQuant Flow Cytometer by Miltenyi Biotec.


Identifying opportunitiesIn order to overcome variability of difference cell manufacturing lots, the process must be fool-proof. With a simplified device handling 90-95% of manufacturing, this is reducing in-process control and quality control. Such a device should of course increase reproducibility and robustness, and should be easily transferable to various sites. This would go hand-in-hand with software providing interconnectivity between manufacturing and quality monitoring to control manufacturing processes. When we compare to jet engines, such as Rolls Royce, data is collected in a central hub so that as the technologies come online, they are providing helpful feedback to monitor and control the system.

Online analyticsThe decentralisation of the qualified person (QP) would also imply that software based solutions would need to be developed, such as full electronic batch records. Additionally, a second layer of control and the question around liability were discussed as products flow across geographical borders and regulatory jurisdictions.

What does this mean for the industryFor the general success of cell and gene therapy approaches, such as CAR-T, there needs to be a high transparency in manufacturing and supply of these cell therapies to ensure effective patient management by clinicians and investigators. Whether these cell products are manufactured centralised, in regional hubs, or at point of care is primarily irrelevant for patients.

There are already concepts for decentralized manufacturing testing within clinical trials, but whether such approaches are financially viable or can be handled adequately by, say, a qualified person (QP) is open for debate. New tools need to be developed and implemented, particularly on the quality control and software side, to allow for more freedom in thinking.

The key lesson from this chapter…Solutions in health care for cell and gene therapy manufacturing should primarily focus on patients’ needs and should keep the patient perspective in mind. Part of developing such complex medicines is the open and transparent dialogue with all stakeholders, including patients and clinicians.


CHAPTER ELEVEN WHICH TOOLS, PLATFORMS AND PROCESSES FOR GENETICALLY MANIPULATING CELLS WILL WIN OUT IN CELL THERAPY?

Calley Hirsch, PhD Development Scientist II, CCRM

Calley Hirsch leads the team optimizing the closed CAR-T manufacturing process for CCRM and GE Healthcare and has previously driven efforts surrounding the development of upstream lentiviral production strategies.

“Defining and implementing the correct scalable automation strategies are key next steps for improving process robustness and final product consistency in cell and gene therapy manufacturing.” Calley Hirsch, PhD, Development Scientist II, CCRM

Spencer Hoover, PhD Development Manager, CCRM

Spencer oversees analytical development for both internal and client projects as well as disruptive technologies including in-line sensing and automation of specific cell therapy processes.

“Small, simple automation steps can go a long way towards improving cell and gene therapy manufacturing by reducing variability in process and decreasing the likelihood of contamination.” Spencer Hoover, PhD, Development Manager, CCRM

Overview Cell engineering methodologies are routinely applied across the cell and gene therapy industry to modify and/or reprogram cellular function for therapeutic benefit. Many clinical advancements and initial therapy approvals continue to rely on complex manufacturing processes to produce payloads and deliver new genetic material. These can suffer from high costs and labour requirements, safety concerns, poor efficiency and consistency. Accordingly, the development of automated manufacturing solutions that can address these challenges is quickly becoming a priority for the next generation of cell and gene therapies.

Manufacturing improvements surrounding genetic engineering are necessary for the advancement and lasting success of cell and gene therapies. Cell engineering is employed through a variety of viral and non-viral methods, each with a unique set of process challenges.

In this chapter, current cell engineering workflows are used to discuss the short and long-term priorities (and value add) of automation states from process advancement and regulatory perspectives. These are looked at in the context of lentiviral (LVV), adeno-associated virus (AAV) production, directed nuclease editing and non-viral nucleic acid delivery to support cell engineering.

Viral vectors The majority of CGTs currently employ viral vectors (LVV or AAV) for ease of gene delivery, but these therapies are saddled with high costs due to the inefficient, variable, complex, and difficult to scale viral manufacturing processes. These typically depend on transient transfection of adherent serum-based cultures, often with multiple manual vector collections, complex downstream purification processes, and lengthy analytic release assays.

There has been a recent push to automate viral vector production, by adapting cells to microcarrier cultures or suspension-based serum-free growth in bioreactors. These bioreactor platforms offer major advantages, such as;

• Enabling closed in-line culture controls

• Scalability

• Improvements in transfection consistency

• Continuous perfusion

• Viral harvest capabilities with reduced labor and contamination risk


However, coupling automated in-process transient transfection methods to bioreactor cultures remains a challenge and a priority if we are to drive batch consistency and completely close the upstream viral vector production process. The development of stable and inducible viral producer cell lines offers a secondary solution which would benefit from integration of a high throughput automated screening platform to identify producer clones of interest in a shorter timeframe.

From a downstream virus purification perspective, numerous bespoke processes have been designed to avoid high vector losses and to have minimal automation support, although high throughput vial and bag filling of purified viral doses followed by controlled freezing and storage are short-term automation priorities.

Remaining automation considerations for viral workflows revolve around analytic capabilities. These include a pressing desire to automate cell density, viability and transfection efficiency measurements and more challenging long-term initiatives to develop automated real-time analytic platforms to monitor empty vs. full AAV capsids, and infectious LVV vector yield and purity

Directed nucleases The use of directed gene editing with targeted nucleases, such as TALENs, ZFNs and CRISPR/Cas9 is gaining momentum across allogeneic CGTs, yet challenges associated with low editing efficiency and specificity, a long iterative tool design process, and non-ideal safety testing prevent the widespread adoption of these technologies for autologous therapies.

Modified automation platforms based on the Biopharma cell-line design industry are in development to improve screening strategies. The next priority is to adapt these platforms to expedite the lengthy manual design phase by adding high-throughput single cell capabilities for rapid specificity, and off-target detection assays in reference to non-edited cell counterparts and predicted natural genomic variation.

Nucleic acid delivery Non-viral introduction of nucleic acid to target cells is most commonly mediated by physical cell disruption or chemical carrier methods and has historically demonstrated poorer genetic delivery efficiency compared to viral vectors.

Given the complexity and high cost of viral production as well as the safety concerns surrounding random viral integration, parallel efforts have focused on improving non-viral delivery efficiency for cell and gene therapies.

Early automated solutions (including flow electroporation instruments) have been designed for this purpose as have other physical microfluidic devices and automation platforms for the assembly of encapsulated nucleic acids in lipid nanoparticles (LNPs) for delivery. A number of these devices have been designed to accommodate scalability needs that offer improvements in non-viral delivery efficiency.

Automated integration with other unit operations, safety testing, data output and analytics are quickly becoming important next priorities as the cell and gene therapy field anticipates pivoting away from viral-based therapies in the coming years.

What’s preventing us from fully realizing the potential that cell engineering offers? What gaps are preventing therapeutic manufacturers from fully realising the potential that cellular engineering offers? Largely these gaps are focused around the needs for tools and reagents that would make cellular engineering cost-effective, reproducible at manufacturing scales and compliant with regulatory guidelines. Once automated cellular engineering solutions are in place, cellular modifications will be used throughout the manufacturing process.

CAR-T therapiesA major cost driver of autologous T-cell therapies is the lentivirus used to deliver the CAR to patient-derived T-cells. Automated solutions are needed to improve transduction efficiencies which in turn will reduce the amount of LVV needed per dose while maintaining or improving the potency on a per cell basis. The transduction process itself can be highly variable due to the innate variability of patient derived cells and LVV batches. Any automation of this process that reduces variability would be a benefit to all autologous manufacturers using LVV.


Allogeneic therapiesDifficulties in cellular engineering for large batches of cells presents in two separate ways.

Approach 1 is to engineer the starting cell line prior to expansion. This approach allows for selection of specific cells and is typically done at a smaller scale, making the reagent costs much lower. However, this process is still almost entirely manual and open (similar to making a master cell bank) and automated solutions for colony picking and small-scale expansion are quite limited.

Approach 2 is to scale-up prior to engineering the cells. This provides some advantages in automation by using bioreactors to carry out the transfection or transduction as well as allowing for scale-up to be a platform process. Drawbacks to engineering after scale-up include significant reagent costs for a 50L or 200L process and difficulty in ensuring that a high percentage of the cells have been successfully engineered. Tools and reagents that improve the efficiency of introducing nucleic acids into cells at large volumes are a major need for the field.

All cell and gene therapiesAs the first generation of successful cell and gene therapies make their way onto the market, engineering needs for both autologous and allogeneic therapies have been identified. These needs include;

• Automated, near real-time monitoring of which cellular populations have been edited

• Improved design of nucleic acid sequences that can predict expression of genes and off-target effects

• Large amounts of GMP-grade mRNA and DNA plasmids for genetic engineering

• Reduced costs by service providers will greatly accelerate the field

While many of the automation needs are immediate for cell and gene therapies, there is great potential for applying genetic engineering in new and novel ways. Some therapeutics manufacturers are investigating ways to use cellular engineering to increase treatment potency, enhance cell population selection, drive down manufacturing and reagent costs, and improve reproducibility and safety. These advances will help to further revolutionize disease treatment.

What does this mean for the industry?Introduction of automated strategies to cell and gene therapy manufacturing is a relatively new initiative for the industry. At the unit operation level, a number of automated approaches have led to advancements in cell engineering workflows but integration of these solutions is still lacking.

While short- and long-term automation priorities are discussed independently for viral vectors, directed nuclease gene editing and non-viral nucleic acid delivery, the majority of interest lies within developing scalable automated viral vector and analytic manufacturing solutions to deliver on more cost-effective and consistent cell and gene therapy products in the short term.

Strategies aimed at reducing process variability linked to viral vector batch and patient cell inconsistencies, such as the development of more robust automated upstream production and transduction processes are also needed along with near real-time analytics to measure in-process variation.

Automation priorities for non-viral delivery should also be highlighted as a pressing need, albeit for a smaller cohort of the cell and gene therapy population. Even more niche are automated directed nuclease platforms – perhaps indicating that the industry may be many years removed from adopting non-viral cell engineering and targeted gene modification approaches over viral based gene engineering.

The key lesson from this chapter…The current automation desires of the field are mostly focused on ways to drive down the cost of viral vector production and the amount of virus needed for autologous therapies. Additional gene editing techniques are still in early days and have great potential to create transformative therapies as manufacturing challenges are solved.


CHAPTER TWELVE FROM FACTORY TO PATIENT: WHAT AUTOMATED TOOLS DO WE HAVE AND WHERE ARE NEW INNOVATIONS NEEDED?

Rodney Neal Vice President, Strategic Program Management, Werum IT Solutions

Rodney’s career has focused on improving manufacturing enterprises through the application of operation (OT) and information (IT) technologies which enable a dynamic, flexible and responsive supply chain.

“Commercial scale cell-based therapy products present some of the most unique and critical requirements in manufacturing. The stakes are too high and the need too great to leave the challenge unmet” Rodney Neal, Vice President, Strategic Program Management, Werum IT Solutions

Ohad Karnieli, CEO, Founder, ATVIO Biotechnology

Dr Karnieli earned his PhD focusing on cell and gene therapy from Tel Aviv University and an MBA from Haifa University. Having served in several executive roles in the fields of cell and gene therapy and medical devices, he is a well-known process development and automation expert. Ohad is the founder and CEO of ATVIO Biotechnology.

“The cell and gene therapy industry is nurturing cutting edge science but lacks the technologies to reach desired levels of maturity. This gap can be filled only by innovation; the current tools used by the industry were not specifically developed for these processes and any automation designed around them will never meet our needs in quantity and quality.” Ohad Karnieli, CEO, Founder, CCRM

OverviewThe speed at which new Advanced Therapy Medicinal Products (ATMPs) are coming to light is breath-taking within an industry where innovation is normally measured in decades. The nature of cell, gene and tissue engineered therapies has introduced a whole new layer of complexity to the traditional pharmaceutical industry scale-up challenges.

Many of the early products are autologous in nature and require GxP compliance of the entire supply chain, including transportation and logistics, while maintaining chain of identity and cold chain management type assurances. In parallel, advancements in automation technology have contributed to improvements in manufacturing, logistics, tracking and data management.

Given the plethora of challenges and the relative immaturity of the processes supporting these new therapies, three primary questions came to mind when considering the portion of the value chain from “factory to patient”:

i) What are the challenges for scale-up/out?

ii) Where are innovations needed the most?

iii) What automated tools are available?

When addressing the cell and gene therapy value chain there are at least four separate and distinct perspectives that drive opinion of improvement potential via automation. These are;

1. Manufacturing (e.g. process engineer, technical roles)

2. Support (e.g. clinician, quality, researcher roles)

3. Business (e.g. operations, business support roles)

4. Supply chain (e.g. logistics, distribution roles)

The results of the session’s poll at Phacilitate’s Automation SIG (Fig.14) illustrate that the two functions with the most potential for improvement are manufacturing and support.


Fig.14 Outcome of audience poll when asked “Which portion of the factory-to-patient value chain could most benefit from automation innovation to facilitate scale-up/ scale-out?”

1. Business processes (e.g. scheduling, logistics, reimbursement)

2. Manufacturing (e.g. fill-finish and packaging)

3. Supply chain (e.g. storage/ thawing at pharmacies)

4. Support processes (e.g. quality such as product review/ release or compliance, patient delivery systems, clinical outcome reporting and analysis).

The opportunities for each function were characterised by addressing three questions for each. The responses are neither prioritised nor weighted.

The view from manufacturing i) What are the challenges of scale-up/out?

• Variability in labware design and material composition affects control rate freezing processes

• The innovation cycle for cell and gene therapy is compressed; e.g. going from lab to pilot to commercialisation could be as short as three years as opposed to small molecule or biotech development cycles of ten to fifteen years

• The compressed development cycle and supply chain and manufacturing challenges of CTG require information that is accessible across the entire value chain. The term “lab to patient” is sometimes used to refer to the scope of information required to support normal operation and advancement of this segment of life sciences

• Cell cryopreservation is difficult to automate e.g. large batches of allogeneic product

• The fill finish and packaging processes present challenges at scale

• “Traditional” mindsets are impediments to progress. Maybe we need to think in terms of how to eliminate cryopreservation as opposed to automating it

• Managing network flow between closed system processes

• The industry should coalesce around some standard manufacturing processes to the mutual benefit of all parties

ii) Where are innovations most needed?

• Standardisation of packaging and labeling which enable downstream optimisation and scalability e.g. vial bags

• Formula optimisation to allow packaging in the most effective and clinic-ready formats

• Method and framework for evaluating contamination risks and product integrity of different approaches e.g. closed system, clean-rooms, aseptic filling, integrated nodes, etc

• Automated scalable manufacturing systems

• Methods for transfer that reduce contamination potential


• Cryogenic and sterile tube-level storage e.g. Brooks Life Sciences

• Centrifugation based segregation and volume reduction

• Cell expansion systems

Cell and gene therapy companies should investigate other industries to see what may be applicable vs. “reinventing the wheel” e.g. leverage RFID technology for tracking.

The view from support processesi) What are the challenges of scale-up/out?

• Paper based quality record reviews are a bottleneck. One SIG manufacturing participant indicated that they spend around 27 hours in batch record review. In autologous cell and gene therapy one batch equals one patient. A Qualified Person (QP) has to review and sign-off on all paper documents

• The quantities of assays are an issue in autologous therapies for the same reason stated above for quality record reviews

• The requirement to validate the end-to-end process including the complete vein-to-vein supply chain pushes traditional regulatory (e.g. FDA) boundaries. The challenge is to define commercial procedures which support validation at scale around these processes

• The complexity of the process requires quality personnel to be knowledgeable across a broad range of subjects. The industry probably requires leveraging automation technology such as artificial intelligence to reduce product and production status to red / green dashboards


• Establishing and maintaining GxP compliance in clinical settings (e.g. good clinical practice (GCP) at an apheresis site or infusion site, etc.)

• Staffing and training of qualified persons will rate limit progress of the industry

• Staffing and training of clinical sites involved in these advanced therapies

• The system of record is more complex than batch records for traditional product manufacturing

• Boundaries need to be established between custodial agents e.g. hospital, manufacturer, transportation and pharmacy

ii) Where are innovations most needed?

• An end-to-end integrated view of the product

• Artificial intelligence or other advanced technologies that can assist humans in tracking, monitoring and ensuring compliance of cell and gene therapies

• Quality review processes which are exception based in near real-time

• Work instructions integrated with batch record collection in support of the concept of instructional batch records (IBR) vs. electronic batch records (EBR)

• A data model of the complete end-to-end process which promotes sharing of an integrated view in support of analytics. Regulatory agencies must govern the end-to-end data model. A regulatory agency participant emphasised that the data must be traceable to a patient defined for a marketable authorisation and retained for a minimum of 30 years in a format that can be recalled

• Enhanced sensors to measure and collect information; e.g. industrial internet of things (IIoT)

• Visibility of the product in the supply chain; e.g. the oncologist and patient should be aware of shipment status for a therapy


• Basic sensors in support of IIoT data collection and analytics

• Automated thawing systems

What does this mean for the industryWhile cell and gene therapies are a relatively new segment of medicine, the challenges are well within view, as is the substantial potential for positive impact to human health. While visibility of these benefits is a strong motivator from a humanitarian and business perspective, the challenges are still quite daunting.

The key recommendations for this chapter are;

• Cell and gene therapy products require new processes. The processes are relatively immature and must advance quickly to sustain the business and realise their full potential.

• Collaboration around development of standard processes is beneficial to the entire industry.

• Data collection and sharing are required to feed the innovation cycle and sustain operability, cell and gene therapies are a data intensive pursuit.

• Cell and gene therapy quality requirements are different. Quality professionals must be an integral part of the team, engaged early and all must be prepared to expect complicity.

• The overriding emphasis is “getting the right product to the right patient”. This is an order of magnitude more complex than traditional drug manufacturing and distribution systems. There is no margin for error.

• There is a great need for an intellectual and procedural framework for evaluating and mitigating risk that recognises the unique characteristics of cell and gene therapies.

• Due to the complexity of challenges, there is a need to develop advanced technical tools such as Artificial Intelligence to aide humans in managing the processes.

• Staff recruiting and development is a potential rate-limiting impediment to scale due to the speciality nature of the CGT.

They key lesson from this chapter…“The last 50 meters is out-of-control”

Frequently the term “vein-to-vein” is used to characterise the scope of the cell and gene therapy process. This term is borrowed from hematological based autologous therapies such as CAR-T. The last few steps in the process are critical and present great opportunities for improvement.

39

8-9 May 2019 | Milan, Italy

Documents

Phacilitate Automation SIG: 2018 Report · 2019. 3. 1. · Phacilitate Automation SIG: 2018 Report 1 FOREWORD Since the inaugural Automation Special Interest Group (SIG) in 2017 the