A Framework and Case Study for Implementing the New Process Validation Guidance

Transcription

1 A Framework and Case Study for Implementing the New Process Validation Guidance Presented By Bikash Chatterjee President and Chief Technology Officer Pharmatech Associates

2 Agenda Introduction Comparing the New Process Guidance to the 1987 Guidance Pharmatech's Roadmap Case Study Questions? 2

3 Overview of the New PV Guidance Issued in January 2011 Based on experience gathered by the FDA since 1987 Radical departure from the original concept of process validation Scientific understanding in order to control process variability Integrates basic principles of ICH Q8 and Q9 3

4 Who is Affected by the Guidance? Manufacturers will be directly affected by the changes if they sell products into FDA regulated markets in the following categories: Human drugs Veterinary drugs Biological and biotechnology products Drug constituent of a combination drug/device Both finished product and active pharmaceutical ingredient (API) manufacturers are affected 4

5 Process Validation Definition For years, many in the industry have been able to recite the FDA s 1987 definition of process validation. The 2011 guidance has updated the definition and shifted the focus from documentation to scientific evidence throughout the product life cycle 1987 Definition 2011 Definition establishing documented evidence which provides a high degree of assurance that a specific process will consistently produce a product meeting its pre-determined specifications and quality characteristics the collection and evaluation of data, from the process design stage throughout production, which establishes scientific evidence that a process is capable of consistently delivering quality products 5

6 Ramifications of the Validation Product Lifecycle The life cycle approach to validation has significant impact on manufacturers who previously have seen validation as a discreet effort at the commencement of product commercialization For many companies, core validation activities have been IQ, OQ, PQ and 3 process validation batches. The FDA is keen to move firms away from this thinking. Indeed the guidance states: Focusing exclusively on qualification efforts without also understanding the manufacturing process and associated variations may not lead to adequate assurance of quality. Verifying adequate assurance of quality will involve assessment of all three stages described in the guidance. This will significantly increase emphasis on prequalification activities such as product development, as well as assessment of procedures for, and results of ongoing process verification 6

7 Equipment Qualification While there is now less focus on what equipment qualification activities are called, there is little difference between the requirements of the old and new guides, as illustrated in the table below 1987 Guidance 2011 Guidance Describes Installation Qualification which, in practical terms, refers to IQ, OQ and arguably equipment PQ. The 1987 guide does not mention OQ or equipment PQ Describes Process Performance Qualification which, in practical terms, refers to equipment PQ (if not previously covered) and prospective process validation batches Describes Equipment Qualification which, in practical terms, refers to IQ, OQ and equipment PQ Describes Process Performance Qualification which, in practical terms, refers to what we would think of as prospective process validation batches 7

8 The New Process Validation Guidance Stage 3 Process Monitoring Stage 1 Process Design 2011 FDA Process Validation Guidance Stage 2 Process Qualification Stage 1: Process Design Define the Knowledge Space Identify Critical Process Parameters Determine Control Strategy Stage 2: Process Qualification Equipment/Utility/Facility Qualification Process Performance Qualification Stage 3: Continuous process Monitoring Monitoring of Critical process Parameters as part of APR and other Monitoring programs 8

9 The Three Golden Batches The new guidance makes it clear that it is the manufacturer s responsibility to provide assurance that the process is adequately qualified. The use of statistical methods to provide objective evidence of this is strongly recommended In practice, this may mean that 3 batches is sufficient to provide the necessary data, or it may be that more are required (it is unlikely to be less). The manufacturer needs to assess, justify and clearly state those requirements during the preparation of the PPQ protocol 9

10 Matrix Approach The 1987 guidance expressly discouraged matrix approaches to process validation, where multiple similar products, presentations or equipment are grouped together Conversely, the 2011 guidance provides specific acceptance of the practice, stating: Previous credible experience with sufficiently similar products and processes can also be considered. 10

11 Concurrent and Retrospective Validation The concept of concurrent validation was not included in the 1987 guidance The new 2011 guidance provides information on the precise circumstances under which concurrent release of validation batches is acceptable. These include: 1. infrequent product manufacture 2. necessarily low volume or short shelf-life manufacture (e.g. radiopharmaceuticals) 3. manufacture of medically necessary products in short supply The FDA expects that concurrent validation approaches will be used rarely. If used, the approach must be fully justified and additional expectations for customer feedback and stability are required 11

12 Legacy Products The 2011 FDA guidance states: Manufacturers of legacy products can take advantage of the knowledge gained from the original process development and qualification work as well as manufacturing experience to continually improve their processes. Implementation of the recommendations in this guidance for legacy products and processes would likely begin with the activities described in Stage 3. In the end there can only be one standard for validated products Firms must develop a plan to bring all products up to the same level of control 12

13 Pharmatech s Technology Transfer Roadmap Product Design Establish PAR/NOR Process Understanding CPPs/Risk Assessment Historical Performance Equipment Design Process Reproducibility PPQ Prerequisites Point... Point... Point... Point... Point Point Point Point PPQ Risk Assessment Verification Process Monitoring Continuous Improvement Risk Assessment Verification Characterization Studies Change Control and Stage 3 Recommendation 13

14 Case Study 14

15 Case Study Application 15

16 Lexicon Critical Process Parameter (CPP): A process parameter whose variability, within defined limits, has an impact on a critical quality attribute and therefore should be monitored or controlled to ensure the process produces the final drug product quality Critical Quality Attribute (CQA): A physical, chemical or microbiological property or characteristic that should be within a predetermined range, range or distribution to ensure the desired final product drug quality Critical To Quality Attribute (CTQ):An in-process output parameter that is measured and/or controlled that should be within a predetermined range, range or distribution to ensure the desired final product drug quality 16

17 Stage 1 Process Understanding Product Design Process Risk Assessment Equipment/Process Characterization Studies Sampling Plans Sampling Techniques Method Robustness Design Space Establishment Validation Master Plan 17

18 Product Design Why go back to product design? Understand what is important: Product Requirement Specification (PRS) Have solid grasp of formulation and product design rationale Formulation may provide insight as to which processing steps are critical downstream Rationale for product design helps define how the formulation, raw materials and process steps are related to achieving desired product performance 18

19 Key PRS Specifications Key criteria from the PRS include: Greater than 50 percent Active Pharmaceutical Ingredient (API) Round 200 mg tablet Coated to mask taste 12-hour drug release with the following specifications: 4 hour dissolution percent 8 hour dissolution percent 19

20 Raw Material and API Considerations Consider existing qualified Suppliers when choosing excipients Includes a review of products with similar PRS requirements Foundation for Knowledge Management effort API characterization includes Supply Chain and Quality Engineering feedback from current products 20

21 Tablet Formulation API Raw Material Microcrystalline cellulose %w/ w Function 60 Active ingredient 22 Excipient filler Povidone K Granulation binder Lactose 12 Excipient filler Mg Stearate 1 Lubricant Purified water QS Solvent Coating Solution Raw Material %w/w Function Eudragit Coating Solution 12 Controlled release polymer Triethyl Citrate 1 Plasticiser Talc Water 1.5 Glidant QS Solvent 21

22 Process Risk Assessment Helps identify which processing steps could affect process stability in Stage 2 Process map to capture inputs, outputs, and control variables Process FMEA s to prioritize key process steps and KPIV s Critical to Quality Attributes(CTQs) identified Helps focus characterization studies 22

23 Risk Assessment Process Map Identify formulation driven PRS requirements Establish boundaries for the process step risk assessment Identify controlled and uncontrolled variables Establish basic measurement approach Separate between scale independnet and dependent varaibles Conduct risk map Review development data Analyze historical performance to set acceptance criteria Develop Process Map Identify CPP/CTQ/CQAs Development/ Historical Data Gap Analysis 23

24 Process Unit Operation Risk Assessment CQA Process Steps Granulation Drying Milling Blending Compression Coating Appearance Low Low Low Low Medium High Assay Low Low Low Medium Low Low Impurity Low Low Low Low Low Low Blend Uniformity Low Low Medium High High Low Drug Release Low Low Low Medium Medium High Particle Size Medium Low High Low Low Low Distribution Justifications for High Rating N/A N/A Milling screen size and speed can affect the PSD and therefore the powder flow and tablet fill weight control Blending can affect blend uniformity, assay, and drug release profile Compression can affect drug uniformity in the tablet based upon particle size variability and flow The final appearance and drug release rate are affected by the coating quality and reproducibility 24

25 Relationship Between Proven Acceptable Range and Normal Operating Range Max Set Point Run(s) Target Set Point Variability of actual data around set point PAR NOR Limit of individual excursions Min Set Point Run(s) Duration of process 25

26 Historical Analysis The absence of development data establishing the PAR and NOR for the CPP can be ascertained to some extent by evaluating the historical behavior of each parameter along with the corresponding behavior of the CQAs for the unit operation Data should be extracted from multiple batch records to determine whether the process is stable within lot and between lots The team went back into the batch records of approximately 30 lots across a period of one year to extract the necessary data. This exercise also gave some indication as to whether the parameter was truly a CPP, based upon whether it had an impact on the corresponding CQA for the unit operation Evaluate scale independent and scale dependent parameters 26

27 Control Chart Analyzing Data Process Capability I Chart of PSD Correlation Plot 27

28 Equipment Design Considerations Compare underlying equipment design and configuration differences Focus on impact of equipment design on scale dependent parameters Objective during transfer and scale-up is to understand where equipment can affect the PAR And NOR for the transferred process Also consider final PV considerations such as sampling plans, sampling technique, and method robustness 28

29 Historical data Review Conclusion Dissolution testing of uncoated tablets across the process range were 100% dissolved in 3 hours Storage studies determined bulk granulation and uncoated tablets were sensitive to humidity Operating characteristic (OC) curves developed for each unit operation to understand the relationship between sampling size and sampling risk (AQL vs. LTPD) Highlight sampling challenges prior to design space activity 29

30 Tech Transfer Equipment Comparison 30

31 Unit Operation CPP CTQ CQA Compounding Mixing speed Fully Dissolved- Visual Water temperature Addition rate Fluid Bed Granulation/Drying Spray Rate Inlet Air Humidity Atomization pressure Granulation PSD- Content d 10, d 50, d 90 Uniformity Moisture content Potency LOD Bulk/Tapped Bulk Density Milling Screen size PSD Blending Mixing Speed Content Uniformity Mixing Time Potency-Assay Compression Pre-compression force Tablet Thickness Dissolution profile Compression force Tablet Weight Content Uniformity Tablet Hardness Potency-Assay Friability Coating Spray Rate Percent Weight Gain Atomization Air Pressure Inlet Air Temperature Appearance Dissolution Percentage at 4 and 8 hours Potency-Assay Summary of CPP/CTQ and CQA Assumption for Tech Transfer 31

32 Tech Transfer-Sampling Qualification Sampling Methodology Qualification Gage R&R conducted with sampling equipment for each unit operation. GRR< 20%, Distinct Categories > 5 Sampling Plan Development Could use ANSI Z or Zero-Acceptance Plan. Used Power calculation, e.g. Powered at 80% with 5% as significant difference for a known SD 32

33 Tech Transfer Characterization Study Historical review concluded final product CQA for dissolution is not affected by upstream process before coating Confirmation DOEs are required to establish PAR and NOR upstream with a focus on process predictability Coating process DOE s designed to demonstrate comparability, confirm CPP s, and provide supportive data for PAR and NOR Also included commercial studies, e.g. solution hold time, pan load studies, etc. 33

34 Drug Dissolution Dependence on Coating Weight 34

35 Validation Master Plan Summarizes the rationale for Process performance Qualification CPPs, CTQs and CQAs Summarizes the impact of controlled variables Introduces approach for understanding impact of uncontrollable parameters Justifies sampling plan based upon process risk Defines acceptance criteria based upon product CQA s 35

36 Stage 2-Process Qualification Demonstration phase of the PV cycle Precursors to this stage Facility and utilities that support the process must be in state of control Process equipment must be qualified (i.e. IQ, OQ, PQs are complete) In-process and release methods used for testing must be validated and their accuracy and precision well understood Cleaning validation is complete Essential to have precursors completed to ensure unknown variability is due to process alone 36

37 Stage 2 Process Qualification (cont.) New term: Process Performance Qualification (PPQ) Intended to include all known variables from the manufacturing process Focused on demonstrating reproducibility. This drives the acceptance criteria Cumulative understanding of Stage 1 and Stage 2 No more three lots and we re done Performed as many lots needed to demonstrate a clear understanding of variables and process is in control Data derived from studies will be used to measure manufacturing process in Stage 3 37

38 Establishing Acceptance Criteria Based upon reproducibility criteria For example if the Stage 1 performance for the 4 hr. dissolution was 32% SD= (2%) against a specification of 20-40%: Acceptance criteria could be: 95% confidence interval applied to a spec of 32 ±6% Used a 2 sided t-test with an α= 0.05 (0.025 on the H A for < comparison) We used the ±6% because it is 3 x std. dev. In a normal distribution this covers 99.7 of the data variability for a controlled process 38

39 Stage 3 Continuous Process Verification Goal of this stage is to show assurance that the process remains in control Need monitoring program to detect gradual or unplanned departures from the process Program should be derived from the understanding and knowledge from Stage 1 and 2 to establish alert and action limits Use statistical analysis to determine performance 39

40 Process Validation Deliverables- Legacy Products Review historical performance and risk map Identify predicate process PAR and NOR Identify knowledge gaps for scale dependent variables PPQ Prerequisite reports Tech Transfer characterization studies to establish PAR/NOR Risk map confirmation PPQ studies and recommended CPPs Data gathering protocol Reporting Dashboard/ SOP Summary report Stage 1 Process Design Go/No Go Decision Stage 2 Process Qualification Go/No Go Decision Stage 3 Continuous Process Verification Go/No Go Decision 40

41 Conclusion Technology Transfer must consider the new PV guidance at the outset in order to be able to meet the requirements for Stages 1, 2 and 3 The framework described works equally well for legacy products and newly developed products No single answer to the question of demonstrating process capability. Each firm must define and justify its approach and acceptance criteria for demonstrating reproducibility Quality s role is much more complex in determining suitability and compliance 41

42 Questions? 42

43 Thank You for Your Attention! Bikash Chatterjee President & CTO Pharmatech Associates, Inc Foothill Blvd. Suite 330 Hayward, CA Or visit our website at: 43