Process Performance Qualification. Demonstrating a High Degree of Assurance in Stage 2 of the Process Validation Lifecycle

Transcription

1 Process Performance Qualification Demonstrating a High Degree of Assurance in Stage 2 of the Process Validation Lifecycle

2

3 A LIFECYCLE Approach to Process Validation? Lifecycle [ICH Q8(R2)]: All phases in the life of a product from the initial development through marketing until the product s discontinuation. The Validation Group Management

4 Medical Devices Global Harmonization Task Force Process Validation Guidance Reference The Power of Process Validation in Devices Stage 1 Process Development Large Molecule Development: Always an Enhanced Approach Enablers Stage 2 Process Performance Qualification A High Degree of Assurance PPQ: What could possibly go wrong? Stage 3 - Continued Process Verification Leveraging Quality Planning to Achieve High Level of Assurance The views expressed are solely those of the presenter

5 Quality Management Systems Process Validation Guidance Global Harmonization Task Force Medical Devices Referenced in US FDA Guidance for Industry Process Validation: General Principles and Practices January 2011 Similarities between GHTF and FDA Guidances Similar lifecycle approach Use of statistical methods emphasized Robust Quality Systems expected to support the an on-going state of control The product should be designed robustly enough to withstand variations in the manufacturing process process should be capable and stable to assure continued safe products that perform adequately Process Validation is conducted in the context of a system including design and development control, quality assurance, process control and corrective and preventative action.

6 Process Validation is a term used in the medical device industry to indicate that a process has been subject to such scrutiny that the result of the process can be practically guaranteed

7 Auto-Injector Components: A High Degree of Assurance Injection Molding (Theoretical Example) 12 cavity mold (each cavity = 1 part) 120 second cycle Tool Qualification: Dimensional Inspection 1 part X 0.5 cycles X 60 minutes = 30 parts cycle minute hour hour Cycle Validation X 3: Parameter range high, midpoint, low 12 parts X 0.5 cycles X 60 minutes = 360 parts cycle minute hour hour

8 A High Degree of Assurance Medical Devices Design and Development Controls Process Validation (IQ, OQ, PQ) Monitor and Control / Revalidation Engineering Focus: Adequate component sample sizes = Heavy reliance on statistical methods Biopharmaceuticals Development Process Qualification Continued Process Verification Life Science Focus: Biological systems, few data = Additional measures where statistics alone may be impractical.

9 High Degree of Assurance at End of Stage 2 Stage 1 Development Stage 2 Process Qualification Stage 3 Continued Process Verification Each manufacturer should judge whether it has gained sufficient understanding to provide a high degree of assurance in its manufacturing process to justify commercial distribution of the product. Stage 1 Which and how much data can be used in conjunction with PPQ data to provide confidence the continuing process control? Commercial Manufacturing How much commercial scale data is needed? Established platform manufacturing - Less? Contract manufacturing organizations More? Quality System - Can the quality system support an ongoing state of control? Has Stage 1 process and product knowledge been integrated into the system?

10 Stage 1: An Enhanced Approach in Biopharma The complexity of the molecule and manufacturing processes have necessitated enhanced approaches to development Process Development and Characterization ICH Q8 Cell Line Qualification ICH Q5A, Q5B, Q5D Clinical Manufacturing ICH Q7 Analytical Characterization ICH Q6B Stability Testing ICH Q5C Comparability ICH Q5E Risk and Criticality Assessments ICH Q9

11 Complex Structure and Properties Quality Attributes can be influenced by Molecular Design, Process Design, and Process Control Physiochemical Properties Structural Heterogeneity Post-translational Modifications 4º 3º 1º 2º Impurities Process Related Impurities Product Related Impurities Product Related Substances Degradation Products Biological Activity Contaminants Higher Order Structure Endogenous Virus Immunochemical Properties Adventitious Agents Since the heterogeneity of these products defines their quality, the degree and profile of this heterogeneity should be characterized to assure lot to lot consistency. ICH Q6B

12 It s all about Control Strategy Specifications / Release testing Clinical Justification most important Criticality, process capability and delectability Analysis and Characterization Process characterization Extended product characterization / comparability Process Control and Monitoring Process and product impurities Raw materials Process monitoring / in-process testing Controls, set points, ranges, hold times Process qualification / validation Process Data Tracking and Trending UNKNOWN Derived from: S. Kozlowski, P Swann / Advanced Drug Delivery Reviews 58 (2006)

13 Communicating a High Degree of Assurance Enablers: Standardized Terminology Knowledge Management Quality Systems Quality Planning

14 Perspective on Standardized Terminology it was recognized from both industry and regulators that there is a need for standardized terminology and use of ICH nomenclature when present. There might be a need for additional terms such as.

15 A-mAb Product Lifecycle

16 A-mAb: Criticality Continuum Quality Attributes In development, the degree of criticality may be assigned to quality attributes based on potential safety and efficacy consequences. Following comprehensive assessments of scientific evidence and risk, quality attributes are ranked according to the degree of criticality. The continuum, as opposed to binary classifications of Critical and Non-Critical, is thought to more accurately reflect complexity of structure-function relationships and the reality that there is some uncertainty in attribute classification High Criticality Quality Attributes Low Criticality Quality Attributes Avoids non-critical terminology which may suggest uncontrolled.

17 Quality Attributes: No NONs ICH Q5E: Quality Attribute A molecular or product characteristic that is selected for its ability to help indicate the quality of the product. Collectively, the quality attributes define identity, purity, potency and stability of the product, and safety with respect to adventitious agents. Specifications measure a selected subset of the quality attributes. Quality Attributes Critical Quality Attributes ICH Q6B: Product-Related Substances Molecular variants of the desired product formed during manufacture and/or storage which are active and have no deleterious effect on the safety and efficacy of the drug product. These variants possess properties comparable to the desired product and are not considered impurities.

18 A-mAb Process Parameter Classification Reproduced/Derived from A-mAb Case study

19 Process Performance Input parameters that must be controlled within a narrow range and are essential for optimum process performance. Key process parameters do not affect critical quality attributes.

20 Standardized Terminology: Control and Criticality If a parameter controllability is high risk even within the design space, can this be considered a state of control?? Should a robust control strategy provide assurance that all process parameters are well-controlled?

21 Process Control Strategy Vocabulary Process Variable Control Can the variable be controlled? No Process Output Process Performance Attribute or Product Quality Attribute Yes Process Input Process Parameter Functional Relationships and Parameter Classification Critical Process Parameters Critical Quality Attributes Key Process Parameters Process Performance Attributes Non-Key Parameters Low Risk of Impact

22 Process Performance Attributes Process performance monitoring: Maintaining a state of control Monitoring of product quality attributes alone incomplete - changes in process performance may represent early warning sign Monitored, tracked, trended in Continued Process Verification Process performance attributes demonstrate inter-batch consistency Production Bioreactor Key Parameter: Osmolality Performance Attribute: Antibody Titer IEX Chromatography Key Parameter: Load Conductivity Performance Attribute: Recovery

23 Documentation and Knowledge Management In all stages of the product lifecycle, good project management and good archiving that capture scientific knowledge will make the program more effective and efficient.

24 Turning Documents into Knowledge Engaging the Quality Unit early can be a wise investment in managing documents and knowledge! QA? Engage the Quality Group to enable knowledge management Comprehensively communicating a high degree of assurance through PPQ reports and in S.2.5 is more likely Ensure knowledge integration into the quality system (ICH Q10)

25 Documentation and Knowledge Management Process Development Product Characterization Pilot Scale Production Robustness Studies Risk Assessment Lifecycle Document Development Reports Analytical Reports Batch Records Qualification Reports FMEA Report Technical Summary

26 PPQ Protocols and Reports: Comprehensive Story PPQ documents as tools to describe a high degree of assurance Provide a comprehensive description of the control strategy. Include non-critical process variables even though only a subset of parameters and attributes will comprise PPQ Describe how the subset of PPQ parameters and attributes demonstrates a state of control Reference appropriate stage 1 data and discuss relevance. PPQ Acceptance Criteria How established and why TELL THE WHOLE STORY / MAKE NO ASSUMPTIONS

27 Stage 2: High Degree of Assurance Qualification of Facilities, Utilities, and Equipment Contamination Control Strategy Facilities Flow and segregation Equipment Preventative Maintenance Procedures Changeover Monitoring Environmental, Process Gas, Water Validation Cleaning and Sterilization Membrane & Resin Lifetime Bioburden & Endotoxin Limits (and on-going monitoring)

28 Qualification of Process Performance: Process Control Strategy Specifications, Acceptance Criteria, Action Limits Product Characterization Release Testing Quality Systems and GMP Stability Testing Raw Materials Analysis In-Process Testing Process Controls and Monitoring

29 PPQ Not Limited to Stage 2 Scaled down predictive, qualified models Viral Spiking Studies (ICH Q5) Stage 1 Process Robustness (ICH Q8) Stage 1 Impurity Clearance (ICH Q8) Stage 1, 2 Chromatography Resin Lifetime Stages 1, 2, 3 Extended Analytical Product Characterization Structure Function Relationships (ICH Q6B) Stage 1 Comparability (ICH Q5E) Stages 1, 2, 3 Real Time (Parametric) Release Viral inactivation and clearance parameters Stage 3 Impurity clearance: DNA, Protein A Stage 3

30 Enhanced Sampling During PPQ Routine Samples Characterization-Demonstrates comparability Impurity Clearance Validates small scale models Protein Stability Qualifies non-microbial hold time Capture Viral Inactivation Filtration Cation Exchange Viral Removal Filtration Anion Exchange Filtration

31 Perspective on Enhanced Sampling We recommend continued monitoring and sampling at the level established during the process qualification stage until sufficient data are available to generate significant variability estimates Enhanced sampling and testing to be discontinued after PPQ: PPQ is fully supportive of the predictive small scale models (impurities: Protein A, DNA) Enhanced sampling to continue: Unexpected results obtained in PPQ Trends suspected in PPQ data Plan for data collected FIO (significant variability estimates): Rationale for continued sampling Plan for evaluation of accumulated data Timeframe or amount of data needed to for decision on continuation.

32 Use of Statistical Methods at End of Stage 2 Likely to rely on means other than statistics alone to achieve a high degree of assurance Often insufficient data to correctly apply traditional statistics. Few clinical batches Limited number of commercial scale batches Statistically based sampling plans not useful for homogeneous bulk pools Achieving a high degree of assurance with limited use of statistics requires clear, comprehensive rationale with references to supporting studies conducted in Stage 1.

33 Quality Planning for Commercial Manufacturing What to Measure, Where to use Statistics Action Limits and Acceptance Criteria Statistical Monitoring Thaw Inoculum Expansion Seed Bioreactors Production Bioreactor Quality Plan / CPV Plan finalized at end of Stage 2. What is to be measured and why, accounting for interactions Statistical methods to be used for data evaluation. Frequency with which data will be evaluated Frequency of Management Review

34 Unexpected Results in PPQ Production Chromatography Operations Drug Substance Bioreactor Titre ( ) Recovery Capture (70-100) Recovery AEX (90-100) Process Performance Attributes Recovery CEX (90-100) Acidic Variants (25-35) Quality Attribute Oxidation (3-10) Aggregate <4% Critical Quality Attributes Pilot * % Pilot % Pilot % Pilot % Pilot % Eng Feed Rate / Volume increased after 1 st PPQ run to to increase titer. What next? PPQ % PPQ % PPQ %

35 Unexpected PPQ Results: High Degree of Assurance in Continued Process Verification a reduced number of batches cannot adequately capture the expected process variability at commercial manufacturing scale. To provide continued assurance that the process remains in a state of control throughout the life of commercial manufacturing, we will create a multivariate statistical partial least squares model (PLS) as part of continued process verification.

36 Appropriate Statistical Methods PLS is more powerful than standard univariate Statistical Process Control (SPC) approaches in that it ensures that the internal correlations among the different variables are also considered. For example if at any given time the titer is lower than expected for the measured viable cell concentration, the PCA model will be able to detect this as a potential out of norm signal even if both parameters are within their respective univariate ranges. Thus, a PLS model can be used to create a fingerprint of the process that detects a larger number of potential shifts, trends and excursions that would not be detected by univariate monitoring tools.

37 Quality System: Alert and Action Limits For those parameters that are not built into this PLS model, additional monitoring such as univariate SPC charts, and other routine process monitoring will be carried out. Because of its utility as a process monitoring tool, the PLS model will also have alert and action limits; and when the process result exceeds the action limit a deviation will be initiated.

38 Quality System and Planning Supports CPV Data Collection and Evaluation Trending and Calculations Change Control System Deviation System Complaint System Continued Facility Maintenance Management Review Feedback Loop Adjust Process Feedback Loop Avoid Surprise Feedback Loop Root Cause Feedback Loop No overreaction Qualification Plan / Schedule

39 The A-mAb Case Study Team Abbott Amgen Eli Lilly Genentech GSK MedImmune Pfizer Acknowledgements

40 Back Up

41 Process: Monoclonal Antibody Production Thaw: Working Cell Bank Inoculum Expansion Seed Bioreactors Production Bioreactor Antibodies Produced Harvest- Centrifugation / Depth Filtration Capture Protein A Viral Inactivation Filtration Cation Exchange Viral Removal Filtration Anion Exchange Filtration

42 Quality Group to Enable the KM Program Pharmaceutical Development Technology Transfer Commercial Manufacturing Discontinuation Investigational products GMP Management Responsibilities Process Performance & Product Quality Monitoring System PQS Corrective Action / Preventive Action (CAPA) System elements Change Management System Management Review Enablers Knowledge Management Quality Risk Management