1

Platform Manufacturing of Biopharmaceuticals: Putting Accumulated Data and Experience to Work Table of Contents

1. Objective and Scope 2. Definitions 3. Introduction 4. Platform Manufacturing Approaches and their Application: Phases of

Product Development and Commercial Product Manufacture 5. Leveraging Platform Process and Platform Manufacturing Data Throughout

Drug Development Programs and Manufacturing Operations 5.1 Viral clearance / inactivation steps are usually ‘platformed’ 5.2 A platform process generates data that are relevant to multiple

products 5.3. How much data are required to specify a platform?

6. Presentation of Platform Process Data for Regulatory Review 7. Conclusions

Contributors:

Contributor / Coordinator: Enda Moran, Pfizer Contributor: Wolfgang Kuhne, F. Hoffmann - La Roche Ltd Contributor: Kris Barnthouse, Janssen Biologics Contributor: David Beattie, Merck Contributor: Ranga Godavarti, Pfizer Contributor: Piers Allin, EBE

2

Platform Manufacturing of Biopharmaceuticals: Putting Accumulated Data and Experience to Work

1. Objective and Scope

Technology and process platforms are now used extensively in the biopharmaceutical

industry, both throughout the various phases of product development and in the facilities

used to manufacture clinical and commercial biopharmaceutical products. This document

provides background information on the practical application of technology &

manufacturing platforms within the biopharmaceutical industry. While examples and

references are primarily made to proteins, the principles and approaches may equally be

applied to other biopharmaceutical product classes such as conjugate molecular vaccines,

live viral vaccines and so on. The value of data and knowledge gathered from platform

manufacturing or platform-based process development is explored, and the advantages of

the application and use of platforms, both to drug sponsors and the drug regulatory

agencies, are considered.

2. Definitions

Platform technology / platform process: a common or standard method, equipment,

procedure or work practice that may be applied to the research, development or

manufacture of different products

Platform manufacturing: implementation of standard technologies, systems and

work practices within manufacturing facilities, and their use for the manufacture of

different products

OR

the approach of developing a production strategy for a new drug starting from

manufacturing processes similar to those used by the same manufacturer to

manufacture other drugs of the same type

QbD: Quality by Design

3

IND: Investigational New Drug

IMPD: Investigational Medicinal Product Dossier

EBE: European Biopharmaceutical Enterprises

Mab or mAb: Monoclonal antibody

HCP: Host cell protein

CHO: Chinese hamster ovary

GS-NS0: Glutamine synthetase-NS0

3. Introduction

A platform technology or process may be generally defined as a common or standard

method, equipment, procedure or work practice that may be applied across multiple

products under development or manufacture. For example, ‘platform’ may be used to

refer to an expression system such as Chinese Hamster Ovary (CHO) cells, a high

throughput screening system based on robotics, an analytical method such as capillary

electrophoresis, a drug product formulation, a mode of cell culture such as perfusion

culture, a process unit operation such as affinity chromatography or even a complete

process comprising multiple unit operations, Figure 1.

Figure 1 Examples of different types of platform-based tools or methods

in biotechnology product development and manufacture. The

term ‘platform’ can be applied broadly.

A cell line (expression

system) Robotics

Affinity

Capture

(ProA)

Ion

exchange

(AEX)

NanofiltrationCentrifuge UF/DF

A process

Low pH

Inactivation

4

The use of platform technologies emerged in biopharmaceutical product

development programs during the 1990s and primarily focused on monoclonal antibody

production processes, Figure 2. As companies’ biologics portfolios expanded to more

than just a few molecules, the benefits of consistency and similarity of tools and methods

across product development programs was becoming apparent. There are multiple

benefits of using platform approaches for development and manufacturing.

Standardisation of approaches and tools across multiple products leads to improved

quality and consistency, substantial cost-savings primarily as a result of more efficient

resource utilisation (equipment/people), and faster process and product development.

Platform approaches provide deep understanding of the impact of the process design and

control stategy on process performance and product quality. This would have benefits in

the implementation of QbD, and in understanding the likely impacts of manufacturing

deviations or process changes. The use of platform technologies represents considerable

opportunities to reduce risk to patient safety, providing access to platform technologies

with proven performance and known safety profiles. Platform technologies applied to a

particular product type, for example monoclonal antibodies (Mabs), introduces a degree

of consistency to the products under development thereby benefitting their process and

clinical development. Modern commercial biotech manufacturing facilities are now

beginning to use platform technologies and standardised work practices to create

efficiencies and flexibility, and to be capable of the manufacture of multiple products

using a consistent set of well-established technologies.

In the past few years, platform approaches have evolved to a mature state within

manufacturing operations of the biopharmaceutical industry. For many reasons,

principally economic ones, commercial manufacturing facilities of the future must be

capable of the manufacture of multiple products. Some newer facilities constructed in

the past few years will have this flexibility built-in, and will have the capability of

manufacturing multiple products usually in a particular product family e.g., Mabs. The

evolution of multi-product facilities will be enabled through the implementation of

standard technologies and work practices within the facilities (platform manufacturing),

5

1990s

2000+

Mature Platforms within process and product development programs

Many manufacturing facilities using platforms and standardised practices and capable of multi-product manufacture

‘New/different’products (to a standard Mab) can still pose implementation issues for manufacture in established facilities

Companies often developing just one lead product

Innovative and research-driven environment

Little focus on ‘manufacturability’. Any of a multitude of technologies selected to make product

No concept of “Platform”

Maturation of Platform Technologies/Processes

Biotechnology products approved

New manufacturing facilities established

Broad array of technologies used e.g., batch, fed-batch, perfusion (multiple systems), roller-bottle culture, different cell lines etc. – ‘whatever worked!’

‘Inflexible’ facilities

First Platform approaches introduced within company development programs

1980s 1990s

1990s

2000+

Mature Platforms within process and product development programs

Many manufacturing facilities using platforms and standardised practices and capable of multi-product manufacture

‘New/different’products (to a standard Mab) can still pose implementation issues for manufacture in established facilities

Companies often developing just one lead product

Innovative and research-driven environment

Little focus on ‘manufacturability’. Any of a multitude of technologies selected to make product

No concept of “Platform”

Maturation of Platform Technologies/Processes

Biotechnology products approved

New manufacturing facilities established

Broad array of technologies used e.g., batch, fed-batch, perfusion (multiple systems), roller-bottle culture, different cell lines etc. – ‘whatever worked!’

‘Inflexible’ facilities

First Platform approaches introduced within company development programs

1980s 1990s

and the development of similar processes from product to product using standardised

technology and unit operations (platform processes) for transfer into these facilities.

Figure 2 The evolution of platform-based approaches in biotechnology product

development and manufacture. In the 1980s, platform approaches were not

employed. Currently, platforms are widespread within product development

organisations and many production facilities.

4. Platform Manufacturing Approaches and their Application: Phases of Product Development and Commercial Product Manufacture

The pharmaceutical industry is continuously striving to increase the efficiency of

process development in order to move promising products faster and more cost-

effectively into clinical studies. One preferred approach for rapid implementation of

manufacturing processes for new biologics is to develop and implement early-stage

platform processes that are designed to be suitable for the greater part of a company’s

product pipeline. A major intent of the approach is to prevent process development and

clinical material manufacture becoming bottlenecks in the overall clinical development of

new products. For example, production cell lines are created using the same parental cell

6

line, a similar vector and transfection method, and selected using a standardised

approach (usually a high-throughput technology). The final choice of the production cell

line would be based on its performance in the ‘platform process’ using standardized

culture media and culture conditions and the product would be purified using the same

series of downstream process steps: this is different to past approaches to process

development whereby a new process would be developed to accommodate the

recombinant cell line. The product would be formulated in a standard formulation (fixed

buffer composition) and presented in a consistent format, generally lyophilised or liquid.

Process platforms should, by definition, meet a number of a company’s pre-determined

requirements regarding yield, process operability, product quality and so on for early

stage development programs.

A platform manufacturing process used in the clinical development phases would

be expected to deliver the product requirements for supply of phase I clinical studies and

would usually be satisfactory for phase II study supply. In some cases, a need for changes

or improvements might emerge, e.g., to improve the robustness of the phase I process or

to adjust or modify product quality attributes for phase II supply, but these changes would

generally be slight modifications of the platform. Pivotal (phase III) clinical studies are

usually supplied by the final version of the manufacturing process, and often at the

intended manufacturing scale for commercial product supply. Late stage process

development for phase III clinical material manufacture is usually based on the initial

phase I/II platform process. Depending on the company’s development strategy, the need

for optimization, and the availability of alternative innovative technologies, single or

multiple steps of the phase I/II process might be re-developed or optimised in order to

specify the final, commercial manufacturing process.

The platform process concept allows the reconciliation of what might, at first pass,

appear to be incompatible requirements and outcomes of process and product

development. That is, reduced costs and duration of development programs (a concern

7

for the drug sponsors, and the patients waiting for drugs) can be matched with increased

process understanding, increased consistency of quality and heightened assurance of

safety (a concern for patients, the drug sponsors and the Health Authorities). The quality

of a new product can be assessed much earlier in the development process owing to the

availability of standard platform analytical methods which would be evaluated, adapted

and optimized on previous projects. In addition, the knowledge accumulated on previous

projects may be leveraged in order to predict process capabilities under a given set of

operating conditions. The increased process knowledge accumulated from several years

of experience with a platform process therefore creates opportunities to employ QbD-

based approaches to process development, enabling the definition of unit operation and

process design spaces and at the same time, decreasing the development workload for

any given project. These benefits are linked to, and dependent on, the implementation

and use of effective data and knowledge management systems.

Another opportunity is the concept of setting ‘platform specifications’ for new

molecules for those product quality attributes that are common across most, if not all,

mAb programs. The broad experience the industry has with multiple mAb programs in

terms of patient exposure means that the specification-setting exercise for a new program

can be simplified for a number of “standard” attributes by defaulting to a template list of

limits. This would primarily encompass those attributes that are related to “safety” of the

product, for example purity, percent aggregate, percent residual DNA, percent residual

HCP, and endotoxin (if normalized based on highest target dose). In keeping with

regulatory expectations, these specifications could be relatively broad for phase I clinical

programs, so that clinical trial data are acquired with product that has some range of

attribute variability, and then systematically tightened as more manufacturing experience

with the particular molecule is gained and process capability is understood. An extension

of this concept would be to apply “platform specifications” even to those structural

characteristics, such as oxidation, disulphide content, N-terminal and C-terminal

8

modification, glycosylation variants, etc., that have been shown through structure-activity

studies to be not significant for the activity of a particular new product.

Platform processes are currently most established in the biopharmaceutical industry

for the manufacture of monoclonal antibodies. Monoclonal antibodies are regarded as

well-characterized molecules and are known to exhibit very similar physico-chemical

properties. In these cases, development and application of a platform process is regarded

as cost-reducing, efficiency-increasing and in general, accelerative of programs. Most of

the process platforms developed for monoclonal antibodies are based on a standard

process structure: fed-batch cell culture usually in chemically-defined media, clarification

by centrifugation and/or depth filtration, affinity chromatography capture, low pH viral

inactivation step, followed by a combination of polishing steps including an anion

exchange chromatography step (bind/elute or flow-through mode), a cation exchange

chromatography step, a virus filtration step, and the final UF/DF and filtration steps. The

main benefits of an established platform process such as this include;

o Reduction of process development effort, time and costs.

o Prior platform data informs risk assessments on new process weak-points, and

focuses development effort where most needed.

o Consistency in process performance and product quality (especially important

when developing a particular class of products, e.g., monoclonal antibodies

o Simplification of technology transfer activities to production facilities

o Improved asset utilisation: one facility / same equipment for multiple products

o Documentation preparation can be simplified; e.g., only minor adjustments to

production batch records may be required from one process (product) to the next

o Ability to translate learnings from one product to another as process database

grows. Greater significance of a ‘multi-product’ dataset as compared to a ‘one-off’

study on a single product.

o Raw materials and consumables are standardized allowing the use of materials

with safety profiles proven to be acceptable, cost reductions through volume

9

purchasing and waste reduction as inventory stocks may be used across several

different products

o Reduction in time and resources leading up to and including pre-clinical and

clinical studies

o Reduction in failure rates during manufacturing due to accumulated process

experience

o Reduced personnel training burden owing to similar processes and equipment

o Improved speed through repetition

o Routine procedures for in-process and batch release testing lead to reduction of

errors

o ‘Platform specifications’ for early-phase clinical programs

o Broad database and experience to speed troubleshooting of manufacturing

processes

o Preparation of INDs/IMPDs/marketing authorisation applications may be

facilitated more readily: pre-populated templates may be created which reduce

the time necessary for manufacturers to author and prepare the submissions

A platform process should not be regarded as a static, non-changing procedure. Its

performance should be reviewed on a periodic basis. The manufacturer should ensure

that the platform process is delivering a minimum acceptable level of process robustness,

product yield, product quality etc. during clinical development of different products:

these criteria would be developed based on a company’s own specific needs. Changes to

the platform should be introduced through controlled implementation of improvements

and uptake of innovations. Such controls are important to understand the impact of

improvements on the platform.

10

5. Leveraging Platform Process and Platform Manufacturing Data Throughout Drug Development Programs and Manufacturing Operations

The biotechnology industry has matured to the point that many established drug

developers and manufacturers can now claim considerable experience and knowledge

gained through the development and manufacturing of multiple drug candidates.

Extensive and valuable knowledge databases may be accumulated when platform

processes and methods are applied to the development and manufacture of these

biopharmaceutical drugs. Under these circumstances, the question is posed: can we

leverage process and product data gathered across a portfolio of molecules, and apply

these data to the development of similar molecules in the development pipeline? The

benefits of such an approach have been discussed above and include speedier

submissions if certain studies or validations do not need to be executed for each new

product, faster file reviews at the regulatory agency owing to reduced data requirements

in submissions, and greater significance and reliability can be attached to a ‘multi-product’

dataset compared to a one-off study on a single product. Specific examples of platforms,

the data derived from them, and the value of these data are discussed below.

5.1 Viral clearance / inactivation steps are usually ‘platformed’

The viral clearance steps in a mammalian cell-derived biopharmaceutical

manufacturing process are almost always considered when the use of platform process

data/knowledge are discussed. There are good reasons for this. The same virus

clearance studies are executed multiple times under the same protocol on different

protein molecules. The different proteins, especially those from the same ‘family’ of

molecules, e.g., monoclonal antibodies, generally show similar behaviour at the different

clearance steps (filtration/low pH or chemical inactivation/chromatography) which are

operated the same way (platform process) for each product. These repeat studies tend

to yield consistent and similar results from product to product.

11

Numerous published studies have demonstrated the capability of established

downstream process steps for viral clearance. For example, the clearance of the simian

virus type 40 (SV40) at an ion exchange step using Q-Sepharose Fast Flow (QSFF) resin

and under different operating conditions was consistently > 5 log10 for a number of

monoclonal antibody preparations, Table 1.

Table 1 Clearance of the SV40 virus at an ion exchange step using QSFF resin, under different operating conditions and for a number of monoclonal antibody preparations (mAb 1, mAb 2, mAb 3). After Curtis, S. et al. (2003) Generic/Matrix Evaluation of SV40 Clearance by Anion Exchange Chromatography in Flow-Through Mode. Biotechnol. Bioeng., 84, 2, p179

Product Bed Height (cm)

Linear flow rate

(cm/h)

Load capacity (g mAb/L

QSFF resin)

Log10 SV40 clearance ±

95% CIa

Resin type

mAb 1 19 76 50 ≥5.8 ± 0.4 Naïve resin

mAb 1 19 76 50 ≥5.9 ± 0.4 Naïve resin

mAb 1 19 76 50 ≥5.5 ± 0.4 Reused resin b

mAb 2 19 76 50 ≥5.1 ± 0.0 Naïve resin

mAb 2 19 76 50 ≥5.5 ± 0.4 Naïve resin

mAb 2 19 76 50 ≥5.1 ± 0.4 Reused resin b

mAb 3 20 100 100 ≥5.7 ± 0.2 Naïve resin

mAb 3 20 100 100 ≥5.8 ± 0.1 Naïve resin

mAb 3 20 100 100 ≥7.0 ± 0.1 Reused resin b

aConfidence interval. bThe resin was reused more than 50 times under commercial operation conditions prior to

being evaluated for SV40 clearance.

The data in Table 1 are useful reference material to support the principle of

generic or modular viral clearance steps, but a drug manufacturer must develop its own

in-house data to support its case that a step that can be applied to multiple products

without additional testing. The data in Table 2a are from a large drug manufacturer’s

development and marketed product portfolio, and show the inactivation of murine

leukemia virus (MuLV) due to low-pH treatment of suspensions of sixteen different

monoclonal antibodies. After experimentally executing low-pH inactivations for these

12

sixteen different IgG molecules, the step has been proven capable of achieving the

minimum acceptable log reduction values (LRV) under a variety of conditions. These

different conditions including buffer type, monoclonal antibody sub-type, protein

concentration etc. were further examined in range-finding studies to assess the degree of

robustness of the step, Table 2b. Taken together, the body of data is used to specify the

conditions of operation of the platform step.

This determination of the robustness in itself is a useful benefit to the

manufacturer, as no further development or optimisation work needs to be executed on

this platform step. However, there are opportunities to further exploit this rich database.

For example, the data indicate there is little or no incremental value in executing a further

inactivation study on another IgG protein in the pipeline: further data will only verify what

is already proven. Therefore, there is an opportunity to eliminate testing and concentrate

the saved time and expense on other aspects of the development process. Indeed, the

recent CHMP Guideline on Virus Safety Evaluation of Biotechnological Investigational

Medicinal Products (2008) acknowledges that prior experience and data may be used to

support the reduction in virus clearance testing for investigational products under clinical

development. For now, there are clear expectations for virus clearance testing identified

in ICH Q5A (Virus Safety Evaluation of Biotechnology Products from Cell Lines of Human

or Animal Origin), but this opportunity for streamlining and reducing unnecessary burden

in the drug development and regulatory submissions process is an important one to

consider for the near future.

13

Table 2a Low-pH inactivation of murine leukemia virus (MuLV) in suspensions of

different monoclonal antibodies. This biotech manufacturer*

developed a database covering a total of 16 different IgG molecules

covering 2 sub-classes. Targeting an inactivation level of >4 LRV for this

particular step. *Data supplied by member company of EBE

Protein Class Number of

different

proteins tested

Minimum

LRV

Maximum LRV

IgG 16 4.2 8.1

Table 2b Example of a bracketing or range-finding study of parameters

that can impact the performance of the low-pH inactivation of

MuLV. The biotech manufacturer investigated viral

inactivation in experimental designs combining multiple of

these factors and at the indicated levels of these factors. Data

from these types of studies, and those shown in Table 2a, were

used to specify a platform low-pH inactivation step. *Data supplied by member company of EBE

Parameter / Factor

Conditions

mAb Isotype 2 different IgG1

2 different IgG2

Protein Conc. (g/L) 5 20

Buffer type Acetate Glycine

Salt Conc. (mM) 10 150

pH 3.6 (worst-case of range 3.4-3.6)

Temperature (°C) 15 (worst-case* of range 15-25)

14

5.2 A platform process generates data that are relevant to multiple products

The data in Table 3 show the successful application of a platform method for

cleaning of an ultrafiltration system post-use for the processing of two different

monoclonal antibodies. In situations such as this where the protein concentration and

buffer constituents are similar, the platform cleaning method negates the need to

perform cleaning cycle development for each product, with concomitant savings in time,

materials, documentation preparation, and automation system modifications.

Table 3 Application of a platform method for the cleaning of an ultrafiltration system. Only two measures used to assess cleaning performance are shown. Measures are executed post-processing. Examples presented for two different monoclonal antibodies (Mabs). *Data supplied by member company of EBE

Mab 1 Mab 2

* ‘Worst-case’ from perspective of inactivating an enveloped virus

15

Sample Type Acceptance

Criteria Run 1 Run 2 Run 3 Run 1 Run 2 Run 3

TOC Rinse ≤ 1.00 ppm 0.43 0.49 0.26 0.23 0.23 0.23

Endotoxin Rinse ≤ 0.50 EU/ml <0.05 <0.05 <0.05 <0.05 <0.05 <0.05

The data in Figure 3 illustrate the performance of a pilot-scale (thousands L-scale)

platform purification process to deliver similar performance outcomes (in this case, the

concentration of host cell protein (HCP) in the chromatography pools) across a panel of

twelve different monoclonal antibodies. Operational confidence in a platform process

such as this would be further assured through the use of multivariate experimentation in

smaller-scale models of the critical unit operations to verify acceptable and robust

performance when critical process parameters are varied. For many of the reasons

detailed above, achieving this level of consistent performance in a platform process

carries great advantages to the manufacturer and include the ability to plan for successful

campaigns without concern for performance excursions or failures, the opportunity to

speedily ‘switch in-switch out’ products to the production facility and so on. The obvious

question to pose is whether these data could be applied usefully to other products in any

way, thus maximising the value of platform approaches and growing process databases.

Figure 3 Levels of host cell protein in the chromatography step pools during the

downstream processing of twelve different monoclonal antibodies. Abreviations:

Pro A=Protein A affinity capture, BDS=bulk drug substance. *Data supplied by member company of EBE

16

For example (and referring to Figure 3), if a subsequent product (mAb #13) is under

manufacture, the opportunity presents to remove in-process sampling and testing at the

ProA pool for the HCP attribute. Taken further, the process database may expand (more

products) such that confidence of always meeting specification (or target) develops to the

point that all sampling and testing for HCP could be removed. Indeed, and looking at it

from a scientific perspective, a case could be built using platform and product-specific

verification studies to remove the attribute from the final specification list of the

substance or product. Note that HCP is used here as an example but the principle applies

to any process or product-related attribute. Using platform process data in this way

would represent a powerful application of data and risk management to the manufacture

and testing of biopharmaceuticals.

5.3 How much data are required to specify a platform?

There are a number of important and recurring questions to address when

considering the robustness and generic applicability of data derived from platform

operations or platform processes. Firstly, the drug manufacturer will at some point

transition from ‘developing the platform’ to considering the platform specified and

17

established: the question is when this transition occurs? The reality is that this ‘transition’

will depend on the quality and amount of data the manufacturer has gathered on the

platform step or process, and the type of process step or process under consideration.

When we speak of “quality” of data, it is implied that certain types of data such as those

from multi-factorial experimentation will provide greater insights into the degree of

robustness and stability of a process or process step than those data from single factor

studies. Regarding the “amount of data” question, and considering extreme scenarios just

for illustration purposes, it would be difficult to claim a ‘platform’ based on studies or

process runs of just one or two molecules, but when the number of molecules studied

expands to ten or greater as in the example shown in Figure 3 above, the platform could

well be considered established. The amount of data required to verify a platform will also

depend on the characteristics of a process step or unit operation. For example, an

aggressive cleaning regime on an ultrafiltration system dirtied or challenged by a protein

suspended in a simple buffer is unlikely to show substantially varied performance from

one protein molecule to another. In this case, a performance evaluation across two or

three molecules would provide sufficient evidence to the manufacturer that the platform

cleaning step is robust and generically applicable to the processing of similar protein

molecules. In contrast, much more process experience and data would be required if a

platform fed-batch culture step was being developed for a particular class of molecule,

owing to the biological (different cell lines, impact of certain raw materials etc.) and

process variability inherent in this type of unit operation. In summary, there can be no

rigid guiding rules on the amount of data and experience required to specify a platform

process or process step. The drug manufacturer will always be in the best position to

determine for its own particular cases what is appropriate and justifiable based on many

considerations including prior process experience, degree of understanding of the factors

(chemistry, biology etc.) influencing the performance of the process or process step, the

ability to control the process or process step and so on.

The second question concerns platform evolution, and asks whether a change to a

platform step or platform process would constitute a minor modification to the existing

18

platform, or instead, signals the initiation of a ‘new’ platform. Since there is a continuum

of potential changes from minor to major, there can be no hard and fast rules as to what

constitutes a transition to a new platform. For example, and at opposite ends of the

spectrum, a few-degrees centigrade (°C) change in the temperature of the cleaning

solution of an ultrafiltration system would very likely be considered a minor modification

to a platform step, whereas a transition to a new mammalian cell expression system e.g.,

from CHO to GS-NS0, would very likely be considered a transition to a new platform

process. Drug developers and manufacturers that have invested significant years and

resource into developing process platforms tend to carefully modify and adjust those

platforms in stages rather than make frequent, dramatic leaps into new platforms, since in

the latter case, the lengthy phase of data gathering to assess process performance and

robustness would have to start again. Finally, it is worth emphasising the potential value

of the drug sponsor considering early communication with the regulatory agencies to

discuss the justification and rationale for leveraging platform data, if there is to be

significant reliance on platform process data in a forthcoming license variation or new

submission.

6. Presentation of Platform Process Data for Regulatory Review

Regulatory submissions efforts become more efficient through the use of platform

process-based data and knowledge. Internal to companies, templates may be created for

sections of IND/IMPD and commercial licensure submissions which reduce the time

necessary for manufacturers to author the submissions. Regulatory agency reviewers will

also appreciate submissions that make use of platform-based knowledge to demonstrate

more complete understanding of the manufacturing process and the product. Site

inspections, especially for multi-product plants, can also be simplified when platform

approaches have been used, owing to the reduced number of unique manufacturing

19

processes and the concomitant reduction in complexity of the associated quality systems

necessary to manage them.

Platform data should also prove useful to streamline the filing process for post-

approval changes to a manufacturing process or analytical method. For example, in

instances where there is sufficient platform and product-specific evidence that changes to

manufacturing steps and/or equipment or changes to analytical methods etc. have no

impact on the quality, safety or efficacy of the product, then it may be possible to

downgrade the classification of the post-approval submission.

The application of platform-based experience and data to newer products under

development without necessarily having to re-do every study for every product signals a

maturation of the science, experience and knowledge underpinning biotechnological drug

development. While there will always be some product-specific nuances to deal with in

every development program, we are entering the phase of evolution of the industry

where platform data are available to be presented for review to support clinical trial and

marketing authorisation applications. These platform data packages might include those

describing viral clearance capabilities of process steps, clearance of process related

impurities, cleaning regimes for process equipment etc. How might these data be made

available for review? Some possible means are considered here using a viral clearance

step as an example (Figure 4), but as stated previously, the principles are not exclusive to

viral clearance/inactivation unit operations. Current filing structures and mechanisms in

place in many global regions at present do not work as described in Figure 4: this

discussion below is intended to explore possibilities.

Platform-process data could be compiled for multiple products to demonstrate

generic applicability of the viral clearance step. Additional development data could also

be presented, demonstrating the robustness of the step across the intended ranges of

critical process parameters e.g., pH, temperature, time etc. and other process conditions

providing assurance that the step performs acceptably within the operating ranges

20

intended for manufacture. This data package as a whole could be submitted for each

product in each clinical trial application or alternatively, might be lodged in a reference

document similar to a Drug Master File at the agency and would be available for

consultation by reviewers at each new clinical trial application submission by the drug

sponsor. The reference document or ‘Master File’ could be updated by the drug sponsor

if a significant process change was introduced to the viral clearance step, or if a new

replacement clearance step was introduced. If available data were insufficient to support

the generic applicability of the changed or replacement clearance step across multiple

products, product-specific virus clearance data would be submitted under normal practice

until data accumulate to support the step as a platform or ‘generic’ step. The ‘Master File’

would then be updated with new data, and the package applied to subsequent products

under clinical trial or marketing authorisation application.

21

Figure 4 Possibilities for presentation of platform-derived data for regulatory review. A ‘generic’ virus clearance data package is shown as an example, but this illustration could apply to any package of platform process data. Data could be presented for review by submitting the same data package with each new clinical trials application (Path A) or presented once to the agency to be maintained as a type of ‘Master File’ (Path B). The principles shown could equally be applied to Marketing Authorisation Applications.

7. Conclusions

The evolution and benefits of platform technology and processes throughout

biopharmaceutical drug development and manufacture have been discussed. The

benefits of using a platform approach are apparent: standardisation of approaches and

tools across multiple products leads to improved quality and consistency, substantial

cost-savings, efficient resource utilisation (equipment/people) and faster process and

22

product development. Modern commercial manufacturing facilities use

standard/platform technologies and work practices to improve efficiencies and flexibility,

and to be more capable of the manufacture of multiple products. Platform process-

derived data at many drug developers/manufacturers have accumulated to extensive

databases. The biopharmaceutical industry, including the regulatory bodies/health

authorities, is now in a position to exploit these data to improve biopharmaceutical drug

development, manufacture and regulation.