Validation Strategies for Multiproduct Manufacturing

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1 Cleaning and Cleaning Validation Strategies for Multiproduct Manufacturing Facilities John M. Hyde Chairman and Founder Hyde Engineering + Consulting, Inc. Hyde Engineering g + Consulting Europe Limited 22 May 2014

2 Presentation Outline Drivers of Multiproduct Manufacturing Demographic Factors, Tariffs and Trade Restrictions, New Approaches to Cleaning Qualification and Monitoring FDA Process Validation Guidance Three Stages of Validation Importance of Cleaning Cycle Development Lab andpilot Scale Methodologies Commercial Scale Testing Strategies Ongoing Monitoring Statistical i lanalytical lmethodologies Application of PAT to CIP Operations

3 Demographic Factors Life Expectancy Average Life Expectancy has Increased by More Than 50% in BRICCountries Countries Since1940 Increased Rates of Chronic Disease Conditions Age Related Genetic Predispositions Increasing Incomes and Growing Middle Classes Growing Developing World Middle Class Income Translates Into Growing Demand for Biopharmaceutical Products By 2035, More Than 50% of Middle Class Households will be in India and China

4 International Trade Issues Tariffs Many Developing World Governments Impose Heavy Tariffs on Imported Goods Including Pharma Products Pharma Products Manufacturing in Developing Countries are Often Given Preferred Tax Treatment, Especially for Exports Special Economic Zones (SEZs) Other Trade Restrictions Indonesia has Erected Import Barriers, Through Withholding Regulatory Approval, for Pharma Products Imports

5 Developing World Biopharma Manufacturing Incentives Domestic Demand Growing Incomes and Middle Classes Export to Developed Countries Supply of Low Cost Bio Similars Demand to Support International Vaccination Initiatives Growing Demand for Low Cost Per Dose Products Lower Production Costs Labor and Equipment Cost Advantages Shorter Timelines to Bring Facilities Online

6 Factors Impacting Future Bio Manufacturing Higher Titers Less CllC Cell Culture Capacity Required Therapeutic Competition Often Several Therapies for the SameDisease Condition Rheumatoid Arthritis Growth in Vaccine Demand Biosimilars COGS Geographics Global Health Green CO2 reduction Most were not driving forces 10 years ago

7 Cleaning and Qualification Objectives Pi Primary Operational lconcerns Cleaning Consistency Cleaning Quality Cleaning Safety Cost Effective Operations Bases of Assessment of Validation Studies Acceptance Criteria Based Upon Well Understood Design Space Scientifically Proven Operating Ranges Testing Scale Lab, Pilot Plant, Commercial Plant

8 New Approaches to Cleaning Qualification lf and Monitoring Extensive Utilization of Risk Analysis and Management to Establish Focus Areas for Cleaning Validation and Ongoing Monitoring i Development of Existing and New In Process Material Residue Matrix from Laboratoryand and PilotScale Cleaning Data Usage of Residue Matrix Data for Determination of Extent of Full Scale Cleaning Validation Testing (e.g., Utilization of Laboratory Derived Data and Residue Mti Matrices Rth Rather Than Three Full Scale l Runs for Validation of Cleaning for New Products)

9 New Approaches to Cleaning Qualification lf and Monitoring Generation of Product Inactivation Data to Justify Analytical Methodologies for Multi Product Facilities Residue Limits not Based Upon MAC Calculations Unless Residues Contain Significant Levels of Active Drug Product Usage of PAT Methodologies and Data for Basis of Initial Cleaning Validation Studies and On Going Monitoring for Defining i Re Validation i Requirements Utilization of FDA 2011 Process Validation Guidance Approachesfor Bases of Cleaning Validation Program

10 New Cleaning Practices for Cleaning of Multiproduct Process Equipment Re Use of Elastomers Between Manufacturer of Different Products Utilization of Normal Cleaning Cycles Between Manufacturer of Different Products Limited Cleaning Verification Between Manufacturer of Different Products

11 Traditional Approach To Validation Established, Highly Controlled Procedure Three Consecutive, Successful Commercial Runs Confidence Placed in the Consistent Performance of the Controlled Procedure Every Time Some Late Stage Cleaning Cycle Development Often Occurs During Validation At The Time Of Commercial Manufacture Excursions/Deviations i Are Evaluated and Compared to Historical Norms

12 Risk Based Approach To Validation Focused on Cleaning Cycle Development Validation Studies Design and Execution Based Upon Risk Analysis and Management Established Process Design Space Provides Identificationof of CriticalControl Control Parameters and Boundary Conditions for Effective and Tight Process Controls Ongoing Monitoring of Critical Process Parameters Provides Bases of Risk Review and Management With Ongoing Real Time Confirmation of Process Operation Within Validated d Design Space

13 2011 Guidance Based Practices New guidance characterizes process validation ld as a lifecycle rather than a discrete event, as implied in the definition in the 1987 guidance New guidance goes on to say that process validation involves a series of activities taking place over the lifecycle of the product and process

14 2011 Guidance Based Practices New guidance describes process validation activities in three stages Stage 1: Process design Stage 2: Process qualification Stage 3: Continued process verification Stated another way, process validation may be defined as: Process Validation= Lab Studies+ Development History + Commercial Scale Target Values + Ongoing Monitoring

15 Test Plan Stage 1 Cleaning Design Author an experimental test plan describing the approach used to conduct tbench scale cleaning process developmental studies for post production residues. Cleaning Agent Selection Test each residue using a designed experiment to screen alkaline, neutral, and acidic post production residues over a range of typical cleaning process temperatures to determine an appropriate cleaning agent for a particular post production residue.

16 Stage 1 Cleaning Design Cleaning Process Design Space Exploration Using the appropriate cleaning agent, explore combinations of temperature, turbulence, and concentration to assess the response of removal rate over typical ranges of these process variables. Worst Case Residue Evaluation Compare the removal rates of selected post production residues to empirically determine which are worst case with respect to the cleaning process.

17 Essential Cleaning Parameters Cii Critical lcleaning Control lp Parameters (CCCPs) An input cleaning parameter that should be controlled within a meaningful narrow operating range to ensure that cleaning quality attributes meet their specifications. (Out of range results may lead to cleaning failures.) Key Cleaning ControlParameters (KCCPs) An input cleaning parameter that should be carefully controlled within a narrow range and is essential for cleaning performance. Does not affect cleaning cycle efficacy, but may affect the efficiency (utility usage, time, etc.) Critical Cleaning Quality Attributes (CCQAs) An output variable that cannot be directly controlled but is an indicator of cleaning performance and cleaning efficacy.

18 CCCPs and CCQAs for Cleaning Cleaning Process Inputs: Demonstration of Consistent and Real Time Control of Cleaning Parameters, Flow Rate, Temperature, Contact Time, Conductivity, etc. Cleaning Process Outputs: t Demonstration of Ability to Consistently Meet Specifications for Cleaning Quality Attributes, e.g., TOC, Conductivity, Bioburden, Endotoxin, etc.

19 Typical lcip System Analog Instrumentation t ti Essential for Control and Ongoing Monitoring of Cleaning Parameters Factors Affecting Cleaning Efficiency Measured via: Supply/Return Temperature Supply FlowRate Supply Pressure Supply/Return Conductivity

21 Testing Methodology 5 cm ~1 in 2 5 cm Consistent soiling Amount of material Reproducible surface area Control l Dirty Hold ldti Time Cleaning Process Control PID Temperature Control Controlled Agitation Precisely Formulated cleaning solutions

22 Determining Reynolds Number ρ- density μ- viscosity N Impeller speed in revolutions per second D Impeller Diameter Agitated Immersion: D 2 Nρ N = Re μ N Re < 2100 N Re > 3000 Laminar Turbulent Example: T=25ºC D = 2 ( m) ρ = 997 (kg/m 3 ) µ = poise N = 64 rpm (1.07 rps) N Re =

24 Coupon Soiling Representative Post Production Residue Applied to Coupon Soiled Coupon Dried to Simulate Post Production Conditions

25 Coupon Testing

26 Gravimetric Assessment Laboratory Microbalance Accuracy ± grams Tare mass of coupons Amount of residue spiked on coupons Amount of residue remaining after cleaning assessment

27 Range Finding Results Range Finding Tests Rate of Removal [mg/se ec] Water 25C Water 65C COSA CIP 92 25C COSA CIP 92 65C COSA CIP 72 25C COSA CIP 72 65C COSA PUR 80 25C COSA PUR 80 65C Duration [sec]

28 Effects of ph and Temperature Average RemovalRate Rate [mg/sec] COSA CIP 72 [ph2] COSA CIP 72 [ph2] COSA CIP 72 [ph2] Distilled Water [ph7] Distilled Water [ph7] Distilled Water [ph7] COSA PUR 80 [ph7] COSA PUR 80 [ph7] COSA PUR 80 [ph7] COSA CIP 92 [ph12] COSA CIP 92 [ph12] COSA CIP 92 [ph12] Average Removal Rate [mg/sec] % Detergent and Temperature [ C]

29 Surface Response Plot Surface Plot of Rate vs Temp, ph 6 Rate ph Temp 60

30 Box Plot Representation Boxplot of Rate 6 5 Rate Temp ph

31 Contour Plot Representation Contour Plot of Rate vs Temp, ph Rate < > 6 Temp ph

32 Product Fragmentation/Inactivation Conduct Studies to Show Fragmentation / Inactivation of Active Molecule by Cleaning Process Expose Formulated Bulk Product to Cleaning Solutions at Use Strength and Temperature Analyze Residues with SDS Page and Western Blot to Prove Fragmentation / Inactivation Favorable Results Justify Non Product Specific Residue Testing Methods, Re Use of Elastomers and Utilization of Normal CIP Cycles Between Manufacture of Different Products

33 Stage 2 Cleaning Qualification During this stage, the cleaning cycle design is confirmed as being capable of effective and reproducible at commercial ilmanufacturing scale Cleaning cycles challenged with typical post production residues Dirty and clean hold ldtimes also assessed Qualification of the facility, utilities and equipment is required Cleaning systems, clean and plant utilities and process equipmentsystems areofprimaryinterest interest

34 Stage 2 Cleaning Qualification Usually run at operating parameter set points within proven acceptable range or design space Boundary condition testing is not typically performed at this stage as it has been assessed in Stage 1 Requiresadditional QC testing to prove theprocess Qualification testing requires the analyses of many more samplesthanfor ongoingmonitoringof of cleaning Risk analysis used to determine extent of testing requirements Equipment and residue groupings used to determine testing requirements

36 Points to Consider for Cleaning Qualification Analytical Methods Selection Sampling Methods Visual Inspection Residue Limits Role of Risk Assessment in Determination of Extent of Cleaning Qualification Testing

37 Sampling Requirements Are Swab and Rinse Samples Needed? dd? Some Firms Combine Rinse Samples With Rigorous Visual Inspection Only What is the Objective of Each Sample Type? How are Worst Case Sample Sites Identified and Justified? For Rinse Samples, Points of Maximum Cleaning Solution Contact For Swab Samples, Difficult to Clean Areas Due to Physical Constraints or Areas of Residue Accumulation

38 Sampling Requirements Requirements for Rinse Samples Residues Include USP Criteria and What Else? Specific API Residue, Total Protein, Bioburden, Endotoxin? Requirements for Swab bsamples Residues Include Specific or Non Specific Testing (e.g. TOC, Total ProteinorSpecific or Assays)? Swabbing Method Validation Including LOD and LOQ! Recovery Study

39 Visual Inspection Determine Visual Residue Limit (VRL) Establish Critical Parameters Viewing Distance Light Intensity Viewing Angle Lighting Angle Inspector Qualification and Training are Inspector Qualification and Training are Crucial

40 Acceptance Criteria How Clean is Clean Enough? Maximum Allowable Carryover (MAC) Calculations Toxicity or Alergenicity Data LOQ for Analytical Method Cleaning System Performance Role of Product Fragmentation from Exposure to Cleaning Cycle Scientific Rationale Behind Decision?

41 Typical BioPharma Acceptance Criteria Visual No residue present. No pooling or standing WFI. Vessel is visibly clean and dry. Rinse Water Samples Rinse Water Conductivity : 1 10 µs/cm Rinse Water TOC : <0.5 ppm Bioburden: < 10 CFU/100mL to 1000 CFU/100mL Endotoxin:<0.25 EU/mL Surface Samples Surface Swabs : <1 2 ppm TOC in 40 ml Diluent for 100 cm 2 Swabbed Area

42 Risk Analysis and Management Risk Analysis and Management is at the Core of the Primary Objectives of Validation Risk Analyses Provides the Bases for the Focus of the Process and Cleaning Validation Programs Risk Management Provides the Means for Ongoing g Assurance of Consumer Safety and Product Efficacy Process Analytical Technologies (PAT) Can Provide Risk Rd Reduction Through h Enhanced dprocess Understanding di and Real Time Failure Detection

43 Document The Risk Assessment

44 Stage 3 Continued Cleaning Verification Ongoing assurance that t cleaning is in control Monitor, collect information, assess, continuous verification, cleaning process improvements No longer revalidation, instead ongoing periodic evaluation 21 CFR (e) Annual review to determine whether changes in specifications or manufacturing or control procedures are needed Study trends, OOS/OOT to make improvements Feedback into design stage for significant process shifts or changes

45 Monitoring Consistency Process Capability Index Capability index is the total specification range divided by the process operating variability, 6σ spread. Cp = total specification/ 6σ = (USL LSL)/6σ Measures how close the process parameter operates to the specification Cp = indicates the process variability consumes only 75% of the specification The specification is 1.33 times the process variability spread Typical Cp goals are

46 Capability Index Amount within Specification

47 Process Monitoring Control Chart Analysis Nelson Rules Lloyd S Nelson, 1984 Western Electric Rules Tests for Out of Control Patterns on Control Charts

48 How Can PAT Apply To Cleaning? Control of Cleaning CCPs Critical for Assurance of Repeatable Cleaning Operations Assurance of Cleaning Operation Within Well Defined Design and Operating Spaces Real Time Adjustment of CCPs for Input Variability Provides Bases for Cleaning Process Improvements

49 PAT: On Line TOC for Cleaning Verification Final Rinse Machine with valves Final Rinse Tank End rinse Provides a finger print of process performance Avoid cleaning failure Avoid excess water use

50 Summary Many Significant Drivers Resulting in Extensive Multiproduct Manufacturing New FDA Process Validation Guidance Provides a Very Good Framework for Effective Cleaning Validation Cleaning Process Development is a Crucial Element Risk Assessment and Management are Key Elements of Program New Approach Results in More Effective Cleaning Qualification and Ongoing Assurance of Cleaning Efficacy PAT Applied to CIP Systems Can Result in Improved and More Reliable Cleaning Operations

51 Contact Info John M. Hyde, B.Sc., M.Sc. Pi Principal i lconsultant Chairman and Founder Hd Hyde Engineering i + Consulting, Inc. john hyde@hyde ec com john.hyde@hyde ec.com

STRATEGIES FOR CLEANING

STRATEGIES FOR CLEANING AND CLEANING VALIDATION THAT MINIMIZE DOWNTIME FOR PRODUCT CHANGEOVERS JOHN HYDE HYDE ENGINEERING + CONSULTING PRESENTATION OUTLINE Importance of Cleaning Process Development at