QBD BIOLOGICS: REGULATORY PERSPECTIVE. 8Jun2015 Mark Alasandro

Transcription

1 QBD BIOLOGICS: REGULATORY PERSPECTIVE 8Jun2015 Mark Alasandro

2 Acknowledgements Thomas Little Dilip Choudhury Curt Monnig Others

3 Outline Regulatory Perspective Building a QbD based Infrastructure Regulatory Governance Guidances Building the Control Analytical Testing Molecule Based QbD for Analytical Methods Modeling -- Linear or Non-linear Stability Key Concerns Lean Stability Approach Summary

4 REGULATORY PERSPECTIVE

5 QbD Principles Target Product Profile Risk Assessment Critical Control Attributes DOE Model Control Strategy Continuous Improvement Knowledge Management

6 QbD Biologics Challenges versus Small Molecules Analytical Method Dependent Small molecule Can determine the structure and the molecules entire makeup from an efficacy and safety perspective. Biologics Can look at amino acid sequence, the secondary and tertiary structure of the protein but really never fully characterize the molecule.

7 QbD Success To date, FDA QbD design space biologic approvals include an expanded change protocol for a drug substance transfer in 2010, and a new biologic (Gazyva) with design space in 2013 (both Genentech)

8 Key Elements of Success Need a clear and logical relationship between QTPP and CQA Well defined Control Strategy (Post-Approval Lifecycle Management (PALM))

9 Regulatory Perspective Need to Show Control Need to show an understanding of the process A mathematical model of the process shows control

10 BUILDING THE INFRASTRUCTURE

11 Building the Company Infrastructure QbD Culture -- company-wide acceptance from the top QbD Champion Development Platforms provide history to build upon Formulation Manufacturing Process Analytical Control Platform Site Transfer QbD Strategy Playbook Forced Degradation Studies/QbD Analytical Methods Technical Design and Evaluation Committee Oversight Governance Senior management Knowledge Management

12 QbD Team Team Formulation Process Analytical Statistics QA RA PAI review process Infrastructure in place for PAI

13 REGULATORY GOVERNANCE GUIDANCES

14 Regulatory Perspective Key Governing Guidances QbD ICH Q8 (R2), Q9, Q10, Q11 Q&A and Implementation Guide Process Validation FDA Guidance 2011 Specifications ICH Q6B Stability ICH Q1A Q1E ICH Q5C 21 CFR USP general chapters <1049> and <1046> biopharmaceuticals and cell and gene therapies, respectively

15 ICH Q8, Q9 and Q10 Q&A and Points to Consider Quality Implementation Working Group on Q8, Q9 and Q10 Questions & Answers (R4) Current version dated November 11, 2010 ICH QUALITY IMPLEMENTATION WORKING GROUP POINTS TO CONSIDER (R2) ICH-Endorsed Guide for ICH Q8/Q9/Q10 Implementation Document date: 6 December 2011 Discusses Model

16 Regulatory Perspective EMA guidelines CPMP/QWP/609/96: Declaration of Storage Conditions CPMP/ QWP/2934/99: In-Use Stability Testing (applies to products in multidose containers) CPMP/ QWP/159/96: Maximum Shelf Life for Sterile Products After First Opening or Following Reconstitution

17 Regulatory Perspective Publications and Presentations EMA-FDA pilot program for parallel assessment of Quality-by-Design applications: lessons learnt and Q&A resulting from the first parallel assessment, 20 August 2013 EMA/430501/2013, Human Medicine Development and Evaluation Questions and Answers on Design Space Verification, October 2013, EMA/603905/2013

18 QbD FDA Presentations Role of Models in the Quality by Design (QbD) Paradigm: Regulatory Perspective, Sharmista Chatterjee, Ph.D., October 23, 2011, AAPS Annual Meeting Quality by Design Approaches to Analytical Methods -- FDA Perspective, Yubing Tang, Ph.D., October, 2011, AAPS Annual Meeting QbD Approaches and Analytical Procedures Yubing Tang, Ph.D. FDA/CDER/ONDQA IFPAC, Arlington, VA January 24, 2014 Implementation of Quality by Design A Regulatory Perspective Sarah Pope Miksinski, Ph.D. Division Director (Acting) Division of New Drug Quality Assessment 2 FDA/CDER/OPS/ONDQA, DIA. Jun 2014

19 Regulatory Perspective Rest of the World Guidances World Health Organization ASEAN: Association of Southeast Asian Nations Emerging markets outside the ICH region ANVISA: Brazil China South Korea

20 FDA Accelerated Approval Initiatives Guidance for Industry Expedited Programs for Serious Conditions Drugs and Biologics (May 2014) Accelerated Approval Fast Track Priority Review Breakthrough Therapy

21 ANALYTICAL TESTING MOLECULE BASED BUILDING THE ANALYTICAL TOOL KIT

22 Biologics QbD Design Based on Molecule Monoclonal Antibodies Proteins Antibody-Drug Conjugates Combination Products Cell and gene therapies High concentration biologics

23 Selecting Analytical Tools Molecule Based Antibodies, Proteins Structure NMR FTIR UV circular dichroism X-ray crystallography of the fc region Monosaccharide analysis Sialic acid analysis Oligosaccharide profile N-glycan analysis Aggregates SEC, SEC-MALS Sedimentation velocity analytical ultracentrifugation Purity Capillary gel electrophoresis Charged variants Isoelectric focusing, IC Function/Bioactivity TNF, SPR, C1q Thermal Stability DSC

24 Analytical Tool Molecule Based Protein instability Deamidations (hydrolysis of asparagine and glutamine side chain) Oxidation of methionine, histidine, cysteine, tyrosine and tryptophan residues Aggregation (association of monomers or native multimers covalent or noncovalent) Glycoproteins (most common instability of glycosylation hydrolysis of sialic acid residues) Impurities in formulation and excipients

25 QBD FOR METHOD DEVELOPMENT AND VALIDATION METHOD OPERATING RANGE DESIGN SPACE FDA-EMA Collaborative Research on QbD for Analytical Methods Initiated Jan, 2013 QbD Analytical Filing Success

26 Analytical Method Risk Assessment Based on molecule, what are the key analytical tools needed Define Critical Analytical Attributes Mark S. Alasandro, Thomas A. Little, Jeffrey Fleitman, Method Validation by Design to Support Formulation Development, Pharmaceutical Technology, Volume 37, Issue 4, pp , Apr 2, 2013

27 Design Space from the 3 Factor Case Study: API Percent Recovered versus amount of Excipient 3 in formulation

28 The top Contour Profile is a plot of Precision (Mean Std Dev) versus Bias (Mean Percent Recovery 100%). Any combination of precision and bias that falls in the white space will give acceptable results. The bottom Prediction Profiler is a tool where Bias and Precision can be varied by moving the cross hairs to determine the impact on % Acceptance Rate. Mark S. Alasandro, Thomas A. Little, Process and Method Variability Modeling to Achieve QbD Targets, AAPS PharmSciTech, submitted

29 What is Modeling Being able to predict Some examples Challenges in Applying to Biologics Based on type of molecule Not directly measuring the active as with small molecules

30 Why Do We Need Modeling Required in guidances Increased in-licensing and acquisition late stage development compounds 65% of 41 Molecular Entities approved in 2014 were in-licensed or acquired. 25% of the 41 were antibodies, peptides, and enzymes (3 out of 27 were biologics in 2013) FDA accelerated approval initiatives Reduced R&D resources

31 Examples Linear Non-Linear

32 LINEAR ACCELERATED MODELING Yan Wu, Anita Freed, David Lavrich, Ramesh Raghavachari, Kim Huynh-Ba, Ketan Shah and Mark S. Alasandro, Bringing Drug Product Marketing Applications to Meet Current Regulatory Standards: Trials and Tribulations", AAPS PharmSciTech, in press

33 Linear events Degradation Aggregation Deamination Oxidation Etc.

34 Linear Fit

35 Fit Model Software

36 Model of Expiry Predictions for Linear Profile Based in Linear Model Can Predict Expiry Based On Any Temperature

37 NON LINEAR ACCELERATED MODELING MOISTURE INGRESS/EGRESS, LEACHABLES, DISSOLUTION Application of the QbD (Quality by Design) Approach for Coating Drug Eluting Stents (DES) Martin K. McDermott, FDA/CDRH/OSEL/DCMS & Sharmista Chatterjee, FDA/CDER/OPS/ONDQA IFPAC 2014 Annual Meeting 23 January 2014

38 Non Linear Changes Packaging moisture ingress/egress Leachables Dissolution Stent coating procedure Implants Yan Wu, Anita Freed, David Lavrich, Ramesh Raghavachari, Kim Huynh-Ba, Ketan Shah and Mark S. Alasandro, Bringing Drug Product Marketing Applications to Meet Current Regulatory Standards: Trials and Tribulations", AAPS PharmSciTech, Mark S. Alasandro, Thomas A. Little, Multifactor Non-linear Modeling for Accelerated Stability Analysis and Prediction, Pharmaceutical Technology, Volume 38, Issue 7, pp , Jul 2, 2014

39 Non-Linear Profile Drug Release Based on Storage Temperature

40 Non-Linear Profile Modeling the Profile

41 Expiry Determination for Non-Linear Models Model with blood levels for a In-vitro in-vivo correlation (IVIVC) Model

42 KEY STABILITY TOPICS TO STAY IN CONTROL

43 Key Stability/Control Topics Photostability ICH Q1B can be used Shipping Studies USP Good Distribution Practice Guidance Chapter 1087 In-Use and End-Use Studies Temperature Excursions Use Force Degradation Studies to support Emerging Characterization Methods Analytical Developments for Control Strategies Lean Stability

44 Summary Need to show understanding of how to control Mathematical Modeling is one approach Need to confirm it is accurate Need to build an analytical tool kit to get the best characterization of the molecule Need to build the internal commitment to a QbD approach

45 THANK YOU Questions?