Use of QbD Principles for the Development of an Integrated Control Strategy. CMC Strategy Forum Europe May 22-24, 2017 Girish J. Pendse Ph.D.

Transcription

1 Use of QbD Principles for the Development of an Integrated Control Strategy CMC Strategy Forum Europe May 22-24, 2017 Girish J. Pendse Ph.D.

2 Background Integrated control strategy includes analytical, upstream, downstream and facility (e.g. micro) control strategies Control strategy was developed following ICHQ11 (i.e. Development Manufacture of Drug Substances) and incorporates aspects from several other ICH guidance documents Concepts and methodology presented were successfully implemented to support the approval of a multiple monoclonal antibody processes in the US, EU and ROW countries 6/26/2017 Company Confidential 2012 Eli Lilly and Company 2

3 Control Strategy Components 1. Overview of how control strategy was developed 2. Process Description Example 3. List an example of Critical Quality Attributes (CQAs) for the process 4. Control Points Matrix 5. CQA acceptance criteria for key process intermediates 6. Methodology of parameter classification and PAR establishment 7. Summary of CPPs, critical limits and Proven Acceptable Ranges (PARs) 8. Summary of operational process parameters (OPPs) and corresponding operating ranges 6/26/2017 Company Confidential 2012 Eli Lilly and Company 3

4 1. Conceptual Flow of Control Strategy Evolution Perform Risk Assessment of Potential Impact of Process Parameters on CQAs Perform Empirical Studies of Selected Parameters Informed by CQAs Determination of Process Parameter Criticality Process Parameter Classification and Determination of Proven Acceptable Range 6/26/2017 Company Confidential 2012 Eli Lilly and Company 4

5 2. Process Description Example Unit Op 1 Vial Thaw & Flask Expansion Unit Op 2 Unit Op 3 Scale-Up Bioreactor Expansion Production Bioreactor Cell Culture (Upstream) Unit Op 4 Centrifugation & Depth Filtration Unit Op 5a Protein A Capture Unit Op 5b Unit Op 6 Unit Op 7 Unit Op 8 Low ph Viral Inactivation TFF #1 Polishing Step Viral Filtration Purification (Downstream) Unit Op 9 TFF #2 Unit Op 10 API Filtration and Dispense 6/26/2017 Company Confidential 2012 Eli Lilly and Company 5

6 3. Description of CQAs for the Process A molecule specific assessment is needed to identify CQAs which present a potential risk to alter biological activity, efficacy and/or safety The more you understand about the molecule, the better the risk assessment Platform knowledge, prior knowledge obtained during early phase characterization and/or literature in the public domain should be leveraged for the risk assessment 6/26/2017 Company Confidential 2012 Eli Lilly and Company 6

7 3. Example of CQA s for the Process Purity Monomer, High Molecular Weight Species, Low Molecular Weight Species (SEC) (ce) SDS-PAGE Reduced and Non-Reduced Potency Potency Binding ELISA Cell Based Potency Post Translational Modification (Product-Related Impurities) Distribution of major glycans α-gal Sialic Acid Process Related Impurities DNA, HCP, rproa Microbial and Viral Safety Bioburden, Endotoxin, Mycoplasma Viral Safety Genetic Stability 6/26/2017 Company Confidential 2012 Eli Lilly and Company 7

8 4. Control Points Matrix Example Residual HCP Plot Control Points Matrix is a summary of relationships identified between unit operations and their potential impact on CQA s. Control Points Matrix is developed based on available small-scale and large-scale process intermediate data. Harvest ProA/Low ph TFF#1 Polishing Step VF Bulk Residual HCP is cleared by Protein A and Polishing Step unit ops 6/26/2017 Company Confidential 2012 Eli Lilly and Company 8

9 4. Control Points Matrix Example Matrix Table Molecular Characteristics and Product Related Impurity Process Related Impurity Microbial and Viral Safety Critical Quality Analytical Seed Expansion Prod Bioreactor Primary Recovery Pro A Capture Unit Operations Affecting CQAs Low ph TFF#1 Polishing Step Viral Filter TFF#2 Bulk Fill Attribute Method Monomer SEC O HMWS (Aggregate) SEC O LMWS (Degradent) SEC O Charge Heterogeneity (% Acidic Variants) IEC O Charge Heterogeneity (% Neutral Variants) IEC O Charge Heterogeneity (% Basic Variants) IEC O Glycosylation N-Link LC O Sialic Acid N-Link LC O α-gal N-Link LC O Potency Purity by SDS-PAGE Bioassay Non-Red O O Binding Reduced O O DNA qpcr O HCP ELISA O rprotein A ELISA O Colony Bioburden Count O Endotoxin k QCL O Mycoplasma Infectivity O Infectivity xmulv qpcr O MMV Infectivity O PRV Infectivity O O = Point of Origin, - Observed Increase, = Observed Decrease Product Quality Key Intermediates 6/26/2017 Company Confidential 2012 Eli Lilly and Company 9

10 6. Methodology of Parameter Classification and Establishment of PARs Conceptual Flow of Control Strategy Development Early Stage Molecule Specific/ Platform Knowledge Risk Assessment Non-Critical (OPP/IPC) Identify Potential Critical Parameters Preliminary DoE Studies Non-Critical (OPP/IPC) Identify Critical Parameters (CPP/CIPC) & Preliminary PARs Confirmatory DoE Studies Verify CPP/CIPC & PARs Finalize Control Strategy CPP = Critical Process Parameter; CIPC =Critical In-Process Control; OPP = Operational Process Parameter; IPC = In-Process Control; PARs = Proven Acceptable Ranges 6/26/2017 Company Confidential 2012 Eli Lilly and Company 10

11 6. Representative Fishbone Diagrams and FMEA (Example : Unit Operations 1, 3 and 5b) 6/26/2017 Company Confidential 2012 Eli Lilly and Company 11

12 6. Focus on Select Unit Operations (based on Control Points Matrix) Unit Op 1 Vial Thaw & Flask Expansion Unit Op 2 Scale-Up Bioreactor Expansion Unit Op 3 Production Bioreactor Unit Op 4 Centrifugation & Depth Filtration Vial T-Flask Erlenmeyer Flasks Unit Op 5a Protein A Capture N Unit Op 5b Low ph Viral Inactivation N - 3 N - 2 N - 1 Unit Op 6 TFF #1 Unit Op 7 Polishing Step Unit Op 8 Viral Filtration Seed Bioreactor Seed Bioreactor Seed Bioreactor 11,000L Production Bioreactor Unit Op 9 TFF #2 Unit Op 10 API Filtration and Dispense 6/26/2017 Company Confidential 2012 Eli Lilly and Company 12

13 6. Method of Parameter Classification and PAR Establishment Upstream vs. Downstream Methodology Upstream (Unit Op 3) Downstream Model Qualification & Components of Variance Study Model Qualification Parameter Assessment (Ishikawa/Fishbone Diagram) Parameter Assessment (FMEA) Screening DoE and pcpp Selection Univariate Design Screening DoE and pcpp Selection Augmented Design and Response Surface Model Confirmatory DoE and Augmented Design (if necessary) CQA Models Worst-case Simulations for Establishment of Theoretical PARs Viral Clearance Studies Experimental Runs to Confirm PARs CPP Verification and PAR Establishment using CQA Models and VC Studies Finalize Control Strategy Finalize Control Strategy 6/26/2017 Company Confidential 2012 Eli Lilly and Company 13

14 6. Small-Scale Model Development Comparable cell growth, metabolites, process parameters and titer profiles Comparable product quality attributes To Simulate 11K Bioreactors 3L Bioreactor Scale-down Model 11K Commercial Scale Runs To Qualify 3L Scale-down Model Equivalence of Process Performance Indicators (PPIs) Equivalence of Critical Quality Attributes (CQAs) 6/26/2017 Company Confidential 2012 Eli Lilly and Company 14

15 6. Small Scale Model Qualification 3L Bioreactor Components of Variance (CVS) Study (N=18) Equivalence between 3L and 11K Bioreactors Small-Scale Model Qualification (PPIs and CQAs) Small scale (3L) data run at target conditions Large scale (11K) data CVS Inputs: Raw Materials Media and Feed Preps WCB Vials Experiment Block (Time) CVS variance was used for establishment of CQA acceptance criteria used for Screening and Confirmatory DoE Equivalence Test 6/26/2017 Company Confidential 2012 Eli Lilly and Company 15

16 6. Methodology of Parameter Classification and PAR Establishment Approach to Classification of Process Parameters 6/26/2017 Company Confidential 2012 Eli Lilly and Company 16

17 6. Considerations for Practical Significance A statistically significant effect of a parameter against a CQA is informative but is not enough Need to compare the parameter effects against a meaningful scale to determine its practical significance. Both are highly statistically significant effects P< P< CQA CQA Only this effect is of practical significance Process Parameter Process Parameter 6/26/2017 Company Confidential 2012 Eli Lilly and Company 17

18 7. Summary of CPPs, Critical Limits and PARs Types of Control Limits and Establishing Batch Record Ranges from PARs One-Sided Maximum Critical Limit Two-Sided Critical Critical for certain CQAs Critical for certain CQAs Critical for certain CQAs Batch Record Range Proven Acceptable Range Batch Record Range Proven Acceptable Range Company Confidential 2015 Eli Lilly and Company 18

19 8. Summary of OPP s and Corresponding Operating Ranges For each unit op, OPP s were determined after the risk assessment or after the range evaluation study Any process parameter not evaluated in a range study (i.e. not a pcpp based on risk assessment) is classified as an OPP and assigned an operating range equivalent to development and/or manufacturing platform experience Any process parameter which did not demonstrate either statistically or practically significant impact on CQAs is classified as an OPP and assigned an operating range equivalent to the range studied for Screening DoE A subset of OPP s were selected to be monitored for process consistency, e.g. bioreactor transfer viable cell density, downstream unit op yields, etc. 6/26/2017 Company Confidential 2012 Eli Lilly and Company 19

20 Health Authority Feedback on Control Strategy Highlights Predominant theme of questions for earlier filings from US/EU regarding control strategy was provide more detail, i.e. not enough information in filing to provide a complete understanding of all rationale Provide list of all process parameters assessed for each unit op Provide justification for non-critical parameters for all unit ops Provide non-critical parameters that are monitored for process consistency and include in S.2.2 and S.2.4 of Module 3 Provide fish bone diagrams and FMEAs for all unit operations Provide DoE designs, results and analyses for unit ops 6/26/2017 Company Confidential 2012 Eli Lilly and Company 20

21 Health Authority Feedback on Control Strategy Highlights Cell bank related questions Provide acceptance criteria for replacement working cell banks (WCB); provide justification for # of DS lots to support full scale qualification of replacement WCBs Increased focus on cell bank monitoring program Provide more details for cell bank clonality Unit Operation 3 (Production Bioreactor) related questions Provide additional details to support the assertion that the scale down model is representative of the 11K bioreactor in terms of CQAs Provide more details on assessment of practical significance Increased focus on raw material lot-to-lot variability 6/26/2017 Company Confidential 2012 Eli Lilly and Company 21

22 Future Considerations Provide more details for how control strategy was developed in subsequent BLA/MAA filings Proactively, maintain a list of filed OPP s (for future BLA/MAAs) that will be monitored for process consistency For future late phase molecules, integrate DoE studies into early/intermediate stage development to improve process characterization knowledge prior to BLA/MAA filings Continue to track health authority feedback and incorporate into subsequent filings continuous learning 6/26/2017 Company Confidential 2012 Eli Lilly and Company 22

23 Acknowledgements Bioproduct Research and Development (BR&D) BR&D NJ Michael Barry BR&D Indianapolis Tongtong Wang Michael De Felippis Cell Culture Jose Santiago Monique Person Timothy Cavadas Omobolade Ogbuewu Matthew Schwartz Lori Brandt Elizabeth Piotrowski Roseanna Shimansky Sagar Desai Katarzyna Case Denise Cunningham Angel Arrubla Purification Richard Chen Anupama Nalluri Amy Huebner Thomas Tahan Jessica Norton Global Statistical Sciences Anthony Lonardo Alan Richter Ying Zhang Patrick Gaffney Regulatory Petra Cavallaro Edward Saltus Lawrence Starke Formulation Jun Gao Joseph Liu Joel Goldstein TS/MS Dane Dorundo Brian Kearns Christopher Swanson Alex Buttke Robert Klimchak Victor Goetz Bioanalytical Sciences Tim Blanc Ming-Ching Hsieh Tun Liu Babita Parekh Manufacturing Rajeew Gupta Joseph Troiano Anthony Gonzalez Lorraine O Shea 6/26/2017 Company Confidential 2012 Eli Lilly and Company 23

24 Thanks/Questions! Things alter for the worse spontaneously, if they be not altered for the better designedly. Francis Bacon ( ) 6/26/2017 Company Confidential 2012 Eli Lilly and Company 24