Preface -- 1 Analytical Validation Within the Pharmaceutical Lifecycle 1 Phil Nethercote and Joachim Ermer -- 1.1 Development of Process and Analytical Validation Concepts -- 1.2 Alignments Between Process and Analytics: Three-Stage Approach -- 1.3 Predefined Objectives: ATP -- 1.4 Analytical Lifecycle -- References -- Part I Prerequisites -- 2 Data Governance, Data Integrity, and Data Quality 15 R.D. McDowall and C. Burgess -- 2.1 Terminology Used in This Chapter -- 2.1.1 Data Governance -- 2.1.2 Data Integrity -- 2.1.3 Data Quality -- 2.2 Data Governance and Data Integrity Model -- 2.2.1 Descriptions of the Four Levels in the Model -- 2.2.2 Foundation - Data Governance -- 2.2.2.1 Senior Management Involvement -- 2.2.2.2 Policies and Procedures Need To Be in Place -- 2.2.2.3 Roles and Responsibilities -- 2.2.2.4 Quality Culture and Working Environment -- 2.2.2.5 Outsourcing Analysis -- 2.2.2.6 Quality Oversight -- 2.2.3 Level 1: Analytical Instrument Qualification and System Validation (aiqsv) -- 2.2.4 Level 2: Analytical Procedure Lifecycle -- 2.2.5 Level 3: Right Analysis for the Right Analytical Result -- 2.2.6 Quality Oversight for Data Integrity -- 2.3 Interaction Between Levels 1 and 2 -- 2.4 Overview of Data Integrity -- 2.5 ALCOA Criteria for Data Integrity -- 2.6 Understanding Level 3: Right Analysis for the Right Reportable Result -- 2.6.1 Analytical Procedure -- 2.6.2 Trained Analysts Working in an Open Culture -- 2.6.3 Instruments and Systems Used -- 2.6.4 Sample Preparation -- 2.6.5 Time Synchronisation -- 2.6.6 Digitalisation of Sample Preparation -- 2.6.7 Instrumental Analysis by Chromatography -- 2.6.8 Peak Integration -- 2.6.9 Calculation of the Reportable Result -- 2.7 Second-Person Review -- 2.8 Summary -- References -- 3 Analytical Instrument Qualification and System Validation Lifecycle 35 C. Burgess and R.D. McDowall -- 3.1 Data Integrity and Data Quality in a GMP Environment -- 3.1.1 Criteria for Data Quality -- 3.1.2 Regulatory Rationale for Qualified Analytical Instruments and Validated Systems -- 3.2 AIQSV Approach as an Essential Part of the Analytical Procedure Lifecycle -- 3.3 USP General Chapter <1058> -- 3.3.1 Data Quality Triangle -- 3.3.2 AIQ Lifecycle: The 4Qs Model -- 3.3.3 Risk-Based Classification of Apparatus, Instruments, and Systems -- 3.3.4 Roles and Responsibilities for AIQ -- 3.3.5 Software Validation for Group B and C Systems -- 3.4 Enhancement of <1058> and Harmonization of a Risk-Based Approach to Instruments and Systems with GAMP -- 3.4.1 Increased Granularity of USP <1058> Groups -- 3.4.2 Clarification of AIQ Terminology -- 3.4.3 A Continuum of Analytical Apparatus, Instruments, and Systems -- 3.4.4 Mapping USP <1058> Instrument Groups to GAMP Software Categories -- 3.4.5 Enhanced Data Quality Triangle -- 3.5 Risk-Based Approaches to Analytical Instrument and System Qualification [3] -- 3.5.1 Expanded <1058> Instrument and System Categories -- 3.5.1.1 Group A - Apparatus -- 3.5.1.2 Group B - Instruments -- 3.5.1.3 Group C - Systems -- 3.5.2 Examples of Possible Lifecycle Activities for the Eight Enhanced Categories -- References -- 4 Continued HPLC Performance Qualification 51 Hermann Wätzig and Neil J. Lander -- 4.1 Introduction -- 4.1.1 The Importance of Analytical Instrument Qualification -- 4.1.2 Terms and Definitions -- 4.1.3 Continued Performance Qualification: More by Less -- 4.2 Development of the Revised OQ/PQ Parameters List -- 4.3 Transfer of Modular Parameters into the Holistic Approach -- 4.3.1 Autosampler -- 4.3.2 Solvent Delivery System -- 4.3.3 Detector -- 4.4 OQ/PQ Data in Comparison with SST Data -- 4.5 Performance Monitoring: Trending Plots/Control Charts -- 4.5.1 Automated Limit Checking -- 4.6 General Procedure for cPQ -- 4.7 Example -- 4.8 Concluding Remarks -- Acknowledgment -- References -- Part II Establishment of Measurement Requirements -- 5 Analytical Target Profile 71 Brent Harrington -- 5.1 Introduction -- 5.2 Components of an ATP -- 5.3 The Probability Statements -- 5.4 Metrics for Assessment -- 5.5 Summary -- Acknowledgments -- References -- 6 Decision Rules and Fitness for Intended Purpose 79 Jane Weitzel -- 6.1 Introduction -- 6.2 Defining the Fitness for Intended Purpose -- 6.3 Decision Rules -- 6.4 Overview of Process to Develop Requirements for Procedure Performance -- 6.5 Decision Rules and Compliance -- 6.6 Calculating Target Measurement Uncertainty -- 6.6.1 Coverage Factor, k, and Data Distributions -- 6.7 Types of Decision Rules -- 6.7.1 Decision Rules That Use Guard Bands -- 6.7.2 Decision Rules That Use Transition Rules -- 6.8 Target Measurement Uncertainty in the ATP -- 6.8.1 Cost of Analysis -- 6.9 Bias and Uncertainty in a Procedure -- 6.10 ATP and Key Performance Indicators -- 6.11 Measurement Uncertainty -- 6.11.1 What Uncertainty Is -- 6.11.2 Reporting Measurement Uncertainty -- 6.11.3 How Uncertainty Is Estimated -- 6.11.3.1 Step 1. Specify the Measurand -- 6.11.3.2 Step 2. Identify Uncertainty Components and Data Sources -- 6.11.3.3 Step 3. Quantify the Uncertainty Components -- 6.11.3.4 Step 4. Calculate the Combined Uncertainty -- 6.11.3.5 Step 5. Calculate the Expanded Uncertainty -- 6.11.4 Uncertainty Contains All Sources of Random Variability -- 6.12 Example -- 6.13 Conclusion -- References -- 7 Performance Characteristics of Analytical Procedures 97 Joachim Ermer -- 7.1 Precision -- 7.1.1 The Normal Distribution and its Parameters -- 7.1.1.1 But How Do I Know that My Analysis Results Are Normally Distributed? -- 7.1.1.2 So Why Is the Normal Distribution that Popular? -- 7.1.1.3 Student-t-Distribution -- 7.1.1.4 Confidence Intervals -- 7.1.2 The Log-normal Distribution -- 7.1.3 Normal, Not-normal, and Out-of Specification (OOS) -- 7.1.3.1 Out-of-Specification (OOS) Results -- 7.1.4 Precision Levels -- 7.1.4.1 System or Instrument Precision -- 7.1.4.2 Repeatability -- 7.1.4.3 Intermediate Precision and Reproducibility -- 7.1.4.4 Precision of the Reportable Result -- 7.1.5 Calculation of Precisions and Variances -- 7.1.5.1 Analysis of Variances (ANOVA) -- 7.1.5.2 Calculation of Precision from Linear Regression -- 7.1.5.3 Measurement Uncertainty (Error Propagation) -- 7.1.6 Concentration Dependency of Precision -- 7.1.7 Precision Acceptance Criteria -- 7.1.7.1 Acceptable Precision for Assay -- 7.1.7.2 Acceptable Precision for Impurities and Minor Components -- 7.1.7.3 Precisions Benchmarks -- 7.1.8 Precision and Reportable Range -- 7.1.9 Precision Highlights -- 7.2 Accuracy -- 7.2.1 Inference from Precision, Response, and Specificity -- 7.2.2 Comparison -- 7.2.2.1 Significance Tests -- 7.2.2.2 Equivalence Tests -- 7.2.2.3 Direct Comparison (Point Estimate) -- 7.2.2.4 Comparison Examples -- 7.2.3 Spiking Studies (Recovery) -- 7.2.3.1 Percentage Recovery -- 7.2.3.2 Recovery Function -- 7.2.3.3 Standard Addition -- 7.2.3.4 Impurities/Degradants -- 7.2.4 Combined Evaluation of Accuracy and Precision -- 7.2.5 Acceptance Criteria -- 7.2.6 Stability of Sample and Reference Standard Solutions -- 7.2.7 Accuracy Highlights -- 7.3 Specificity/Selectivity -- 7.3.1 Selective Detection -- 7.3.2 Selective Sample Preparation -- 7.3.3 Stress Samples -- 7.3.4 Demonstration of Specificity/selectivity by Accuracy -- 7.3.5 Chromatographic Resolution -- 7.3.6 Peak Purity (Co-elution) -- 7.3.6.1 Re-chromatography -- 7.3.6.2 Diode Array Detection -- 7.3.6.3 Lc-ms -- 7.3.7 Specificity/selectivity Highlights -- 7.4 Response (Calibration Model) -- 7.4.1 Unweighted Linear Regression -- 7.4.1.1 Prerequisites -- 7.4.1.2 Confidence and Prediction Intervals -- 7.4.1.3 Graphical Evaluation of the Calibration Model -- 7.4.1.4 Numerical Regression Parameters -- 7.4.1.5 Statistical Linearity Tests -- 7.4.1.6 Evaluation of the Intercept (Absence of Systematic Errors) -- 7.4.2 Weighted Linear Regression -- 7.4.3 Appropriate Calibration Models -- 7.4.3.1 Optimal Concentration for Single-point Calibration in Case of Impurity Testing -- 7.4.3.2 Area% Quantitation -- 7.4.3.3 Matrix Impact -- 7.4.4 Non-linear Response -- 7.4.5 Calibration Highlights -- 7.5 Detection and Quantitation Limits -- 7.5.1 Requirements in Pharmaceutical Impurity Determination -- 7.5.1.1 General Quantitation Limit -- 7.5.1.2 Intermediate Quantitation Limit -- 7.5.2 Approaches Based on the Blank -- 7.5.3 Determination of DL/QL from Linear Response -- 7.5.3.1 Standard Deviation of the Response -- 7.5.3.2 95% Predictio.

n Interval of the Regression Line -- 7.5.3.3 Approach Based on German Standard DIN 32645 -- 7.5.3.4 From the Relative Uncertainty -- 7.5.4 Accuracy and Precision-based Approaches -- 7.5.5 Comparison of the Various Approaches -- 7.5.6 Quantitation Limit Highlights -- Acknowledgments -- References -- Part III Method Design and Understanding -- 8 ICHQ14 Analytical Procedure Development 219 Phil Borman (GSK), Peter Hamilton (AZ), and Jean-François Dierick (GSK) -- 8.1 Introduction -- 8.2 The ATP -- 8.3 Connection Between Product and Analytical Procedure Understanding -- 8.4 Prior and Platform Knowledge -- 8.5 Robustness and Method Operable Design Region (MODR) -- 8.6 Link and Impact with Analytical Procedure Validation -- 8.7 Analytical Procedure Control Strategy and Ongoing Procedure Performance Verification -- 8.8 Lifecycle Strategy Including Enhanced Approaches in Submission -- 8.9 Summary -- References -- 9 Method Selection, Development, and Optimization 237 Melissa Hanna-Brown, Roman Szucs, and Brent Harrington -- 9.1 Introduction -- 9.2 Method Selection -- 9.3 Method Development -- 9.4 Method Optimization -- Acknowledgments -- References -- 10 Multivariate Analytical Procedures 265 Wei Meng and Phil Borman -- 10.1 Introduction -- 10.1.1 Use of Multivariate Analytical Procedures in the Pharmaceutical Industry -- 10.1.1.1 Product and Process Design Phase -- 10.1.1.2 Control Strategy Development Phase -- 10.1.1.3 Process Validation and Lifecycle Strategy Phase -- 10.2 Sampling and Data Quality -- 10.3 Development of Multivariate Models -- 10.3.1 Data Preprocessing -- 10.3.2 Variable Selection -- 10.3.3 Exploratory Data Analysis -- 10.3.3.1 Principal Component Analysis -- 10.3.3.2 Outliers Detection and Handling -- 10.3.3.3 Cluster Analysis -- 10.3.4 Model Calibration -- 10.3.4.1 Quantitative Modeling -- 10.3.4.2 Qualitative Modeling -- 10.4 Model Optimization and Validation -- 10.4.1 Cross-Validation -- 10.4.2 Mode Performance Assessment -- 10.5 Model Maintenance and Lifecycle Management -- 10.5.1 Ongoing Verification -- 10.5.1.1 Ordinary Maintenance -- 10.5.1.2 Evaluation of Triggers -- 10.5.2 Review Process -- 10.5.2.1 Model Update Assessment -- 10.5.2.2 Model Update Approval -- 10.5.2.3 New Model Version Development and Validation -- 10.5.3 Model Implementation Management -- 10.6 Summary -- Acknowledgments -- References -- 11 Case Study: Robustness Investigations 301 Gerd Kleinschmidt and Birgit Niederhaus -- 11.1 Introduction -- 11.2 General Considerations in the Context of Robustness Testing -- 11.3 Examples of Computer-Assisted Robustness Studies -- 11.3.1 Robustness Testing Based on Chromatography Modeling Software -- 11.3.2 Robustness Testing Based on Experimental Design -- Acknowledgment -- References -- 12 Risk Assessment and Analytical Procedure Control Strategy 343 Phil Nethercote -- 12.1 Background -- 12.2 Risk Management Process -- 12.3 Ich Q9 -- 12.4 Using Risk Management to Develop a Control Strategy -- 12.4.1 Risk Identification/Hazard Identification -- 12.4.2 Risk Analysis -- 12.4.3 Risk Evaluation and Control -- 12.5 Analytical Procedure Control Strategy -- References -- Part IV Method Performance Qualification -- 13 ICH Q2(R2): Validation of Analytical Procedures 353 Joachim Ermer -- 13.1 How to Read This Chapter -- 13.2 Introduction -- 13.2.1 Interpretation -- 13.3 General Considerations for Analytical Procedure Validation -- 13.3.1 New -- 13.3.2 Interpretation -- 13.3.3 Analytical Procedure Validation Study -- 13.3.4 New -- 13.3.5 Interpretation -- 13.3.6 Validation During the Lifecycle of an Analytical Procedure -- 13.3.6.1 Interpretation -- 13.3.7 Reportable Range -- 13.3.7.1 Interpretation -- 13.3.8 Demonstration of Stability-indicating Properties -- 13.3.8.1 Interpretation -- 13.3.9 Considerations for Multivariate Analytical Procedures -- 13.4 Validation Tests, Methodology, and Evaluation -- 13.4.1 Specificity/Selectivity -- 13.4.1.1 New -- 13.4.1.2 Interpretation -- 13.4.2 Range -- 13.4.2.1 General Considerations -- 13.4.2.2 Response -- 13.4.2.3 Validation of Lower Range Limits -- 13.4.3 Accuracy and Precision -- 13.4.3.1 Accuracy -- 13.4.3.2 Precision -- 13.4.3.3 Combined Approaches for Accuracy and Precision -- 13.4.4 Robustness -- 13.4.4.1 New -- 13.5 Annex 2: Illustrative Examples for Analytical Techniques -- 13.5.1 Interpretation -- 13.5.2 Some Specific Gaps -- 13.6 Conclusion -- References -- 14 Case Study: Validation of a High-performance Liquid Chromatography (HPLC) Method for Identity, Assay, and Degradation of Products 373 Gerd Kleinschmidt and Birgit Niederhaus -- 14.1 Introduction -- 14.2 Experimental -- 14.3 Validation Summary -- 14.4 Validation Methodology -- 14.4.1 Specificity -- 14.4.2 Calibration Model -- 14.4.2.1 Calibration Model of mc -- 14.4.2.2 Calibration Model of DP 1 -- 14.4.3 Accuracy -- 14.4.3.1 Accuracy of mc -- 14.4.3.2 Accuracy of DP1 (Degradation Products) -- 14.4.4 Precision -- 14.4.4.1 System Precision -- 14.4.4.2 Repeatability -- 14.4.4.3 Intermediate Precision -- 14.4.5 Loq -- 14.4.6 Reportable Range -- 14.5 Conclusion -- References -- 15 Case Study: Design and Qualification of a Delivered Dose Uniformity Procedure for a Pressurized Metered Dose Inhaler with a Focus on Sample Preparation 391 Andy Rignall -- 15.1 Introduction -- 15.1.1 Analytical Procedures for Complex Dosage Forms -- 15.1.2 Human and Environmental Factors Associated with Complex Laboratory Procedures -- 15.1.3 Delivered Dose Uniformity Testing for Inhalation Products -- 15.2 Designing a DDU Procedure that will Meet an ATP -- 15.2.1 Risk Assessment and Classification -- 15.2.1.1 Device Preparation -- 15.2.1.2 Dose Collection -- 15.2.1.3 Experimental Factors Associated with Dose Collection -- 15.2.1.4 Shaking Profile Experiments -- 15.2.1.5 Actuation Profile Experiments -- 15.2.2 Noise Factors Associated with Dose Collection -- 15.2.3 Dose Recovery and Sample Preparation -- 15.2.4 Automated DDU Procedure -- 15.2.4.1 Automated Shaking -- 15.2.4.2 Automated Actuation -- 15.2.4.3 Automated DDU Procedure -- 15.2.5 Results Calculation and Reporting -- 15.3 Performance Characteristics of the DDU Procedure -- 15.4 Qualification of the DDU Procedure -- 15.5 Summary of the Analytical Procedure Control Strategy for a DDU Procedure -- Acknowledgments -- References -- 16 Case Study: Validation of a Bioassay Method 405 Andrea Sobjak -- 16.1 Introduction -- 16.2 Material Considerations -- 16.3 Study Design -- 16.4 Specificity/Selectivity -- 16.4.1 Stability-indicating Properties -- 16.5 Accuracy -- 16.6 Precision -- 16.6.1 Intermediate Precision -- 16.6.2 Repeatability -- 16.6.3 Reproducibility -- 16.7 Range -- 16.8 Robustness -- 16.9 Conclusion -- Acknowledgments -- References -- 17 Implementation of Compendial/Pharmacopeia Test Procedures 419 Pauline L. McGregor -- 17.1 Background of Pharmacopeia Procedures -- 17.2 How Pharmacopeia Methods Are Generated and Published -- 17.3 Challenges with Compendial Procedures and the Need to Verify -- 17.4 Using Pharmacopeia Procedures in a Laboratory for the First Time -- 17.5 Verification of Pharmacopeia Procedures -- 17.6 Integration of the Verification Process and the Lifecycle Approach -- 17.7 Implementation of a Pharmacopeia Procedure Using the Lifecycle Approach -- 17.7.1 Gather Knowledge -- 17.7.1.1 Define the Intended Purpose of the Procedure -- 17.7.1.2 Understand the Settings on your Instruments -- 17.7.1.3 Read the Monograph Carefully -- 17.7.1.4 Define an Analytical Procedure Control Strategy (APCS) -- 17.7.1.5 Run a Trial Study -- 17.7.1.6 Derive an ATP -- 17.7.1.7 Testing the Feasibility of the ATP -- 17.7.1.8 Finalizing the ATP -- 17.8 Performance Qualification -- 17.9 Conclusion -- References -- 18 Transfer of Analytical Procedures 435 Christophe Agut, Marion Berger, and Hugo Zuin -- 18.1 Transfer Process and Strategy -- 18.1.1 Regulatory and International Guidance -- 18.1.2 Transfer Process -- 18.1.2.1 Coordination of Transfer Activities -- 18.1.2.2 Transfer Strategy -- 18.1.2.3 Familiarization and Training -- 18.1.2.4 Design of Experimental Studies and Acceptance Criteria -- 18.1.2.5 Result Evaluation and Transfer Report -- 18.2 Comparative Testing.

445 -- 18.2.1 Equivalence-based Methodology -- 18.2.1.1 Principle -- 18.2.1.2 Interlaboratory Study -- 18.2.1.3 Transfer Endpoints -- 18.2.1.4 Acceptance Criteria for Equivalence Testing -- 18.2.1.5 Statistical Analysis (Equivalence Data Analysis Methods) -- 18.2.1.6 Decision Procedure -- 18.2.1.7 Illustration of the Approach on a Real Example -- 18.2.2 Direct Comparison -- 18.2.2.1 Precision -- 18.2.2.2 Accuracy -- References -- 19 Lifecycle Approach to Transfer of Analytical Procedures 471 Joachim Ermer -- 19.1 Facilitation of Transfer by Risk Assessment -- 19.2 Facilitation of Transfer by the APCS -- 19.3 "Lean" Transfer Strategy -- 19.4 Conclusion -- References -- Part V Ongoing Method Performance Verification -- 20 Continuous Improvements, Adjustments, and Changes 479 Dr. Phil W. Nethercote -- 20.1 Drivers for Change -- 20.2 Control of Change in the Pharmaceutical Industry -- 20.3 Implementing a Change -- References -- 21 Monitoring of Analytical Performance 487 Joachim Ermer -- 21.1 Sources of Performance Data and Information -- 21.1.1 System Suitability Test Parameters -- 21.1.2 Parameter from Calibration or Reference Standard Analysis -- 21.1.3 Parameter from Sample Analysis -- 21.1.4 Quality Control Samples (QCS) -- 21.1.5 Batch Results -- 21.1.6 Precisions from Stability -- 21.2 Systematic Monitoring Program -- 21.3 Analytical Performance Evaluation Tools -- 21.3.1 Visualization Charts -- 21.3.2 Average Performance Parameters -- 21.4 Assessment of Analytical Performance -- 21.4.1 Immediate Actions -- 21.4.2 Analytical Performance Review (APR) -- 21.5 Conclusion -- References -- Index.