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A 2009 MIT LGO Thesis: Developing the Business Case for Quality by Design in the Biopharmaceutical Industry

A 2009 MIT LGO Thesis: Developing the Business Case for Quality by Design in the Biopharmaceutical Industry. Julie Matthew January 22, 2010 MIT LGO Alumni Web Seminar. Quality by Design is a paradigm shift in industry’s approach to new drug development .

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A 2009 MIT LGO Thesis: Developing the Business Case for Quality by Design in the Biopharmaceutical Industry

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  1. A 2009 MIT LGO Thesis:Developing the Business Case for Quality by Design in the Biopharmaceutical Industry Julie Matthew January 22, 2010 MIT LGO Alumni Web Seminar

  2. Quality by Design is a paradigm shift in industry’s approach to new drug development • A biotechnology industry leader,Amgendiscovers, develops, and produces a variety of human therapeutics • Most products in Amgen’s portfolio are biologics (greater complexity than “small molecules”) • Typical for the industry, Amgen manages a long, complex, and highly regulated product lifecycle from drug discovery to market: • Quality by Design (QbD)is a systematic and science-based approach to drug development (drug discovery through launch) • Not a new concept for most manufacturing industries • Defined in a new pharma/biotech industry standard (ICH Q8) in 2005 • Gaining momentum among innovators and regulators – a QbD strategy is imperative for biotechnology 10-12 Years Drug Discovery Clinical Trials Regulatory Filing Product Launch

  3. Both internal and external drivers have required industry to define the value of Quality by Design • External Drivers: • QbD is gaining momentum among innovators and regulators: a QbD strategy is imperative for biotechnology • Regulatory expectations are increasing; QbD may become “the cost of doing business” • Internal Drivers: • Need to prioritize and/or integrate ongoing QbD efforts • Need to understand the “who, what, and where” in terms of focus and level of investment • Need a collective understanding of major impact areas within the business; determine an appropriate level of investment (enterprise perspective)

  4. Business Case is intended to provide a holistic understanding of the value of QbD • Methodology: • Primary interviews of 40+ SMEs within R&D and Operations at Amgen • Collection and analysis of relevant historical data • Deep-dive project within Drug Product & Device Development • Assumptions • Assess business impact in four key areas of Operations: • Given time constraints, case study not exhaustive but example driven • An integrated approach is critical; to the extent possible, took enterprise-wide perspective Cycle Time Cost Supply Management Compliance & Quality

  5. Framework builds on the philosophy that QbD concepts are broadly applied and have impact to Operations objectives Key Commercialization Elements 3 1 2 4 Technology Transfer Filing & Commercial Production Molecule Selection Process Development & Characterization Cycle Times Cycle Times Cycle Times Cycle Times Compliance & Quality Cost Cost Supply Management Compliance & Quality Investment Benefit QbD is an evolution of “Best Process Development Practices”; early investment yield benefits later in Commercialization as well as for subsequent pipeline molecules

  6. QbD can enhance molecule selection by harnessing the organization’s collective product and process knowledge 1

  7. The mAb Platform leverages prior development knowledge Example 1 mAb Platform • The monoclonal antibody (mAb) platform is a library of knowledge for a common modality • The platform has undergone several revisions since it was first implemented ~7 years ago  Implemented 

  8. QbD can speed commercialization and increase process understanding to meet regulatory expectations 2

  9. Investment in the proper tools allows enhanced, accelerated development using QbD principles Example 2 QbD Tools Lyo Cycle Development With SFD • Cycle prediction in 1 or 2 runs • Real-time temp measurement and adjustment (shorter cycles) Lyo Cycle Development Without SFD • Prior knowledge-based “guess and check” • Conservative approach (longer cycles)  In Progress  80% reduction in resource and time requirements for cycle development Process Characterization Without DOE • Set acceptable ranges • Less focus on parameter interactions Process Characterization With DOE • Focus on critical quality attributes (set design space) • Fewer experiments • Greater process knowledge Design of Experiments  Implemented  30% reduction in resource and time requirements for process characterization

  10. QbD leverages knowledge gained during process development to simplify technology transfer 3

  11. Understanding equipment differences can minimize the need for commercial-scale development work Example 3 • Equipment and method differences are being identified across sites • Knowledge of differences can be used to strengthen validity of scale-down models • Strong scale-down models reduce risk in tech transfer, requiring fewer verification runs at the commercial site Streamlining Fill & Finish Tech Transfer  In Progress  Case Study: AMG-XYZ Fill/Finish Transfer Actual – Pilot-scale data reproduced at commercial scale • Machinability Studies • Validation Runs • 5 Robustness Runs • Engineering Run Opportunity – Valid scale-down model eliminates need for much verification • Machinability Studies • Validation Runs • 1 Robustness Run • Engineering Run Savings: ~1 month in transfer timeline and hundreds of thousands of dollars in resources and raw materials

  12. Integrating QbD principles within commercialization can yield a more robust and flexible process 4

  13. Statistical methods enable real-time control of critical quality attributes, increasing process robustness Example 4 Real-Time Multivariate Statistical Process Monitoring (MSPM)  Implemented 

  14. Statistical methods enable real-time control of critical quality attributes, increasing process robustness Example 4 Real-Time Multivariate Statistical Process Monitoring (MSPM)  Implemented 

  15. QbD yields additional operational benefits Example 4 • Based on review of all Class 2 and 3 NCs between April 2007 and March 2008 • QbD could prevent 7% of NCs • Several hundred thousand dollars cost avoidance annually, not including: • Cost of scrap • Cost of delayed disposition Design space in marketing application: greater flexibility for process changes Non-Conformances Improved process control & greater flexibility from design space • Based on review of all historic Post-Marketing Regulatory Submissions for one Amgen product • 11% of US post-marketing submissions could be prevented with QbD • Several hundred thousand dollars cost avoidance annually, not including: • Cost of inventory accumulation • Cost of supporting studies (e.g., stability and comparability) Post-Marketing Regulatory Submissions • Evaluation based on complaints for one product delivery system since its launch • Total cost of these complaints on the order of several million dollars – potentially avoided with QbD Complaints Improved product quality with a systematic approach to design

  16. Cumulative benefits from these examples represent only a portion of potential savings $ = up to $100K; $$ = $100K to $1M; $$$ = $1M to $10M

  17. The greatest challenge under QbD is alignment Current Approach to Commercialization Ideal State 1 2 Molecule Selection PD & Char. QbD 4 3 Filing & MFG Tech Transfer • QbD emphasizes a strong link between the product and the process; this link should be reflected in commercialization practice • Amgen can maximize the benefits of QbD by integrating processes through: • Knowledge management systems • Business Processes • Communication between elements throughout commercialization • Design for manufacturability • Feedback loops

  18. A knowledge management system could integrate processes and cut waste across the product lifecycle Technology Transfer Filing & Commercial Production Molecule Selection Process Development & Characterization Knowledge Bank • Each element of commercialization can input and access data • Forms of waste that can be eliminated: • Searching for data • Translating data • Recreating existing knowledge • Key Operational benefit: Rapid compilation of data for CTD construction • Majority of the investment will be in data capture prior to TT, filing, and launch

  19. Focused investment in three areas will maximize the benefit of QbD Science & Technology Systems Business Processes QbD Investment = f

  20. Business Case: QbD implementation requires investment across commercialization, but economic and operational benefits would be significant • Internal drivers do exist for QbD in a large biopharmaceutical company • Benefits are operational as well as economic; they are likely underestimated in the business case • Greatest challenges are in alignment of business process, organizational structure, and culture under QbD paradigm • Recommendations: • Promote knowledge sharing across functions and sites • Identify leadership/champions to sustain QbD momentum • Create a cross-functional team to develop a comprehensive internal QbD roadmap • Align internal and external efforts

  21. Acknowledgements • Deborah Wong & Cathryn Shaw-Reid Amgen Advisors • Charles Cooney & Roy WelschMIT Thesis Advisors • Amgen Team and Mentors (among others!): • Joe Halcomb • Bob Maroney • Ed Walls • Erwin Freund • Feroz Jameel • Chakradhar Padala • Christian Ruitberg • Wei Liu • Cenk Undey • Joseph Phillips • Karen Parker • Ricardo Diaz

  22. Questions?

  23. Back-up

  24. Product vs. Process Complexity

  25. Biotechnology industry is more than 10 years behind other industries in applying Quality by Design principles Quality cannot be ensured through inspection and rework, but must be built in through the appropriate design of the process and product http://www.wtec.org/loyola/polymers/c7_s6.htm

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