Challenges Integrating Regulatory Filings and Pre-Approval Inspection with the Expectations of Current Regulatory Guidance

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1 Challenges Integrating Regulatory Filings and Pre-Approval Inspection with the Expectations of Current Regulatory Guidance Tony Mire-Sluis Vice President, North America, Singapore, Abingdon, Contract and Product Quality

2 Recent ICH and Validation Guidance forms a Comprehensive Coverage from Drug Discovery, Development, Manufacturing as well as Detail Regarding Associated Quality Systems GOOD MANUFACTURING PRACTICE GUIDE FOR ACTIVE PHARMACEUTICAL INGREDIENTS - Q7 PHARMACEUTICAL DEVELOPMENT Q8 QUALITY RISK MANAGEMENT - Q9 PHARMACEUTICAL QUALITY SYSTEM - Q10 DEVELOPMENT AND MANUFACTURE OF DRUG SUBSTANCES - Q11 TECHNICAL AND REGULATORY CONSIDERATIONS FOR PHARMACEUTICAL PRODUCT LIFECYCLE MANAGEMENT - Q12 (in development) PROCESS VALIDATION: GENERAL PRINCIPLES AND PRACTICES 2

3 Developing a Modern Quality Management System and Quality by Design is a Theme Throughout the new ICH Guidance 3

4 The Challenge with Current Expectations is the Need to Balance What Goes into A Regulatory Filing Versus What is Available on Inspection Prior Knowledge Continued Process Verification Quality Systems Complex Assay Data QTTP Filing Inspection Risk Assessments 4 Process Characterization Design Space

5 Prior Knowledge Strongly Supports the Product Development Lifecycles Product Design Process Design Process Qualification CPV Prior knowledge Leveraging knowledge across products and lifecycle stages can: Support identification of critical quality attributes Support operating parameter classification Help identify likely sources and magnitude of normal process variability Support effective risk management Guide effective product and process design

6 Reflecting Prior Knowledge in Regulatory Files Presents a Challenge Prior knowledge is extremely valuable because it integrates and builds on vast experience: More than a dozen products at various lifecycle stages, decades of product years experience 100s of manufacturing lots 1000s of raw material lots 100s of DOE studies 10s of thousands of pages of technical reports The challenge is to effectively convey prior knowledge in regulatory files in a manner that: Provides sufficient information to support the data and conclusions Is effective and practical to facilitate Agency review and inspection 6

7 Guidance Discusses the Concept of a Target Product Profile and Products Should be Designed to meet the Requirements Considerations for the quality target product profile could include: Intended use in clinical setting, route of administration, dosage form, delivery systems Dosage strength(s) Container closure system Impacts to clinical efficacy/safety from product quality attributes (e.g. aggregation, oxidation, glycosylation etc.) Drug product quality criteria (e.g., sterility, purity, stability and drug release) appropriate for the intended marketed product 7

8 There are Many Assays That can be Used During Molecular Quality by Design to Achieve a QTTP but how much Research Data is Needs to be Filed? Sequence analysis used to identify protein with desirable attributes t=24h ph jump study performed to eliminate candidates with potential issues in vivo Viscosity (cp) Expression Assessment to achieve high productivity Concentration (mg/ml) Viscosity testing for ease of SC delivery at high concentration

9 Technology May Increase Information Gathered During Product Characterization- But What do we do With it? Yves Aubin, Health Canada Mass Spectrometry Analysis NMR Analysis Such complex profiles make it difficult to set meaningful acceptance criteria if we do not understand what each peak is and whether it is relevant to product quality, safety or efficacy Therefore, new analytical technology, without an understanding of criticality of product attributes could become increasingly burdensome while providing little additional value for risk assessment, safety, etc.

10 Developing a Design Space Involves a Vast Quantity of Data, With Lack of Clarity of how Much is Needed (e.g. non critical process parameters, width of exploration etc.) Prediction Profiler Titer (g/l) ± Galactosylation afucosylation (%) ± ± DNA (ppm) HCP (ppm) ± ± e+6 8e+5 6e+5 4e Aggregates CEX % Acidic (%) Variants ± ± Temperature (C) 50 DO (%) 100 CO2 (%) 6.85 ph [Medium] (X) 400 Osmo (mosm) 12 Feed (X) IVCC (e6 cells/ml) Duration (d) Design space promised nirvana the opportunity to move within a greater set of defined parameters than used traditionally without having to inform an agency allowing for reduced filings, if any, for changes that were within that space The definition of criticality is only defined by the width of the parameters studied, so the agency wants all of that documented However, it has never been clear how to file such complicated equations and get them approved 10

11 A Knowledge Management System is Essential for Continuous Improvement Issue Solutions Prevent significant events Use Case 1 A significant negative event should trigger an alert and drive response and a learning agenda across the company Example Prevent issues occurring across a class of products such as tungsten in syringes, glass lamellae in vials and raw material issues Achieve improvements 2 Employees will seek shared and best practices to enable continuous improvement of day-to-day activities 3 Employees will seek information from knowledge management repository to resolve challenges Search Process Development databases for previous experiences, lessons learnt and best practices Quickly utilize a database to learn guidance, cross company/product for non conformance investigations, supplier issue resolution etc. Efficiently launch new projects 4 Arm the teams with all tools necessary from previous or ongoing programs, files, guidance and literature 11 Team seeks lessons from past programs to identify previous issues and their remediation to prevent occurrence and speed product development

12 Quality Risk Management is now Embedded for Quality Processes, Product Development and Manufacturing Decision Making Maintains the focus on minimizing risk to patients Understanding of the relationship between product attributes and Quality (Safety and Efficacy) Benefits of Quality Risk Management for Quality Directs resources to focus on key development areas that have high impact on product quality Development of robust processes and control strategy to support decision making process ensuring product quality 12

13 Assigning Risk has to be Based on Data and Risk Assessments now Form a Major part of Development and Quality Assurance Compliance Cannot be They Exist Content is Essential Risk Classification Severity of Risk Likelihood of Occurrence 1 Insignificant 3 Minor 5 Moderate 7 Major 9 Severe 9 Almost certain Likely Medium Unlikely Remote Risk Priority Detection Risk Classification 9 Uncertain 7 Remote 5 Moderate 3 High 1 Almost certain 3 High H H H M L 2 Medium H H M L L 1 Low H M L L L A Regulator needs to understand the approach taken by the firm when reviewing Risk Assessments. These can cover hundreds of pages of data. Are summaries sufficient for filings? How do reviewers communicate their review to investigators to ensure one quality voice?

14 Continued Verification will be Defined by a CPV Plan filed in the MA and Relies on the Quality Management System for Control Drop parameters with sufficient data Reduce sampling based on process performance Drop parameters with sufficient data Reduce sampling based on process performance Significant Process Change APR APR APR APR Control Strategy update Control Strategy update # of Parameters Monitored PPQ 30 lots PPQ 30 lots PPQ sampling baseline Change opportunity is with noncritical parameters Baseline monitoring to maintain control Monitoring levels may step down when the process is stable and capable Monitoring levels may step up when we need to monitor more for understanding and control Note: Magnitude of the changes to the monitoring plan are not to scale; they are for illustration purposes only

15 The CPV Plan Will Require the Merger of GMP Compliance, the QMS and Science-based Requirements The new validation lifecycle paradigm of continued process verification requires an upfront plan to be filed, otherwise each of the inevitable changes to PPQ/Stage 3 testing occurring after approval would have to filed in some form rather than simply providing updates in an Annual Report Such a plan relies on the QMS and the Quality Unit to ensure criteria for removal or addition of testing occurs as approved, based on predefined scientific criteria, prior to a review of the Annual Report This blurs the lines of the product reviewer and the GMP inspectorate as both should be looking at such a plan and the processes within the QMS that will execute it, although likely from different angles. 15

16 The Integration of the Quality Management System into the Product Lifecycle is Raising Questions from Reviewers to include more QMS data in Filings Recent additions to filings brought about by questions: Descriptions of the Laboratory OOS/OOT investigation process SOPs regarding Non-Conformances and CAPAs Process Trending programs Action and Alert limit excursion processes Risk Management systems Scoring Remediation activities But will this information inform inspectional activities and how would inspectional findings be communicated back to product reviewers? 16

17 Current Regulatory Guidance and Expectations are Merging the Quality Management System with Traditional Development Data and is Creating Challenges with Filings Versus Inspections Recent ICH guidance pulls together the threads of GMP, QbD and Risk Management and puts them into place for development, execution and the Quality Management Systems There are now many systems that result in huge quantities of data that may not be appropriate to file in their entirety: Prior knowledge Risk Assessments Continued Process Verification data Process Characterization/DoE/Design Space There are increasing expectations to describe relevant sections of the QMS, that have traditionally been reviewed on inspection, into filings Knowledge Management and creating a Learning Organization is essential to modern Quality Management Systems but too much data without relevance or context has limitations for regulatory oversight 17