Quality-by-Design for Biotechnology Products: Facilitating Implementation

Transcription

1 Quality-by-Design for Biotechnology Products: Facilitating Implementation IMPLEMENTATION of QbD and PAT: A REGULATORY PERSPECTIVE An IFPAC-2010 Pre-Conference Workshop Baltimore, MD 2/1/2010 Steven Kozlowski, Director Office of Biotechnology Products OPS, CDER

2 QbD Implementation Link to small-molecule learnings ONDQA pilot and application experience ICH IWG, Q8R, Q9, Q10 ICH Q11 OBP staff participating in conferences, forums and training on QbD Design of Experiments Training Mock Case Studies OBP Pilot

3 Biotech QbD Mock Case Studies EFPIA drafting a case study Industry CMC Biotech Working Group Publishes a QbD Case study (10/31/09) A-Mab: a Case Study in Bioprocess Development Abbott, Amgen, Eli Lilly & Company, Genentech, GlaxoSmithKline, MedImmune, and Pfizer Available on the ISPE Website Nov 2009 Workshops on case study planned (ISPE & CASSS) 278 pages

4 A-Mab is also not. A template for a QbD submission A definitive source of regulatory definitions & terminology The final ideal scientific approach to biotech QbD but it can be. A source of challenging, well thought out examples The basis for discussions and forums likely to contribute to QbD implementation A tremendous effort by Ken Seamon, John Berridge and the top scientific talent of multiple companies Thanks to Anjali Katarina & Conformia

5 pyro-e D O O G D D O G O pyro-e D A-Mab CQA Risk Ranking & Filtering Tool D D Severity = Impact G G x Uncertainty K K Second Tool for CQA & Tool for non-bioactive impurities FMEA Screening DOE Optimization Surface Response Map Occurrence Severity

6 A-Mab Design Space Based on Process Capability Bayesian Reliability Example: Day 15, Osmo=360 mosm and pco2=40 mmhg >99% 7.1 afucos >11% 7 50% contour approximates white region in contour plot confidence of satisfying all CQAs ph p afucosylation Galactosylation (%) Galact >40% ph Temperature (C) Temperature (C) 6

7 A-Mab Engineering Design Design Space for scaleindependent parameters was developed using qualified scaledown models Space Design Space applicability to multiple operation scales demonstrated using PCA/MVA models 500 L 25,000 L RandalAllen 2L Scale Engineering Design Space includes bioreactors of multiple scales and designs (2L -25K L) Based on keeping microenvironment experienced by cells equivalent between scales Includes bioreactor design considerations and scale-dependent process parameters linked to fluid dynamics and mass transfer Importance of PCA/MVA models

8 What is in the Design Space? Load ph Conductivity Are only CQAs used to defining Design Space? Acidic variants used in A-Mab Production Bioreactor Are only CPPs used in a design space? A CPP is a function of the range evaluated (either experimentally or through prior knowledge) 5 o C 40 o C CPP 15 o C 25 KPP o C 18 o C 22 o C GPP

9 OBP Pilot Program FR Notice July 2, 2008 To define clinically relevant attributes for protein products (regulated by OBP) and link them to manufacturing processes To consider quality-by-design (QbD) approaches to unit operations in supplements (10) as well as original applications (5) To explore the use of protocols submitted under - (21 CF (e) and (e)) Notice of Extension of Deadlines and Increase in the Number of Original Applications to 8 Federal Register/Vol. 74, No. 179 /Sep 17, 2009

10 Biotechnology QbD Pilot Status Applications Accepted in QbD Pilot 5 Original Applications 4 Monoclonal Antibodies and 1 Fc Fusion Protein 4 Post-approval Supplements 2 Monoclonal Antibodies, 1 Therapeutic Protein, 1 multi-product One with site tranfers; Working closely with Compliance MAPP OBP & DMPQ Interactions on BLAs OBP QbD Pilot Meetings 6 meetings held with Pilot sponsors More meetings scheduled soon

11 QbD Pilot Meeting Questions 29 questions Questions with subparts were counted separately if they covered a different set of QbD categories or topics 25 associated only with Mabs 4 included other therapeutic proteins Question General categories Design Space 13 Risk Assessment Methods 6 Control Strategy 4 Expanded Change Protocols 4 Small-scale Models 3

12 Risk Assessment Comments Process capability in CQA determination Independence of factors Clarity of terms e.g. critical, key and non-key Consistency in scoring Uncertainty scoring Qualitative versus quantitative scores Justification for severity cutoffs Criticality continuum Use of PK & PD data for attributes Likelihood of interactions For parameters For impurities (e.g. metal & protease)