Joachim Ermer worked for 30 years in the pharmaceutical industry, including analytical development, global responsibilities, Head of Quality Control, and head of QC Lifecycle Management, before he started in December 2020 his consultancy business.

Phil W. Nethercote was the analytical leader for the Global Manufacturing and Supply Division of GSK until he retired in 2016. He has over 30 years of experience in the pharmaceutical industry, the majority of which has been with Glaxo, Glaxo Wellcome and GSK.

Preface xvii 1 Analytical Validation Within the Pharmaceutical Lifecycle 1Phil Nethercote and Joachim Ermer 1.1 Development of Process and Analytical Validation Concepts 1 1.2 Alignments Between Process and Analytics: Three-Stage Approach 3 1.3 Predefined Objectives: ATP 5 1.4 Analytical Lifecycle 7 References 9 Part I Prerequisites 13 2 Data Governance, Data Integrity, and Data Quality 15R.D. McDowall and C. Burgess 2.1 Terminology Used in This Chapter 15 2.2 Data Governance and Data Integrity Model 16 2.3 Interaction Between Levels 1 and 2 21 2.4 Overview of Data Integrity 21 2.5 ALCOA Criteria for Data Integrity 22 2.6 Understanding Level 3: Right Analysis for the Right Reportable Result 23 2.7 Second-Person Review 28 2.8 Summary 30 References 30 3 Analytical Instrument Qualification and System Validation Lifecycle 35C. Burgess and R.D. McDowall 3.1 Data Integrity and Data Quality in a GMP Environment 35 3.2 AIQSV Approach as an Essential Part of the Analytical Procedure Lifecycle 37 3.3 USP General Chapter 38 3.4 Enhancement of and Harmonization of a Risk-Based Approach to Instruments and Systems with GAMP 43 3.5 Risk-Based Approaches to Analytical Instrument and System Qualification [3] 45 References 49 4 Continued HPLC Performance Qualification 51Hermann Wätzig and Neil J. Lander 4.1 Introduction 51 4.2 Development of the Revised OQ/PQ Parameters List 53 4.3 Transfer of Modular Parameters into the Holistic Approach 55 4.4 OQ/PQ Data in Comparison with SST Data 58 4.5 Performance Monitoring: Trending Plots/Control Charts 59 4.6 General Procedure for cPQ 61 4.7 Example 65 4.8 Concluding Remarks 66 Acknowledgment 67 References 67 Part II Establishment of Measurement Requirements 69 5 Analytical Target Profile 71Brent Harrington 5.1 Introduction 71 5.2 Components of an ATP 72 5.3 The Probability Statements 73 5.4 Metrics for Assessment 74 5.5 Summary 76 Acknowledgments 77 References 77 6 Decision Rules and Fitness for Intended Purpose 79Jane Weitzel 6.1 Introduction 79 6.2 Defining the Fitness for Intended Purpose 80 6.3 Decision Rules 81 6.4 Overview of Process to Develop Requirements for Procedure Performance 82 6.5 Decision Rules and Compliance 82 6.6 Calculating Target Measurement Uncertainty 83 6.7 Types of Decision Rules 86 6.8 Target Measurement Uncertainty in the ATP 88 6.9 Bias and Uncertainty in a Procedure 89 6.10 ATP and Key Performance Indicators 89 6.11 Measurement Uncertainty 90 6.12 Example 94 6.13 Conclusion 95 References 96 7 Performance Characteristics of Analytical Procedures 97Joachim Ermer 7.1 Precision 98 7.2 Accuracy 147 7.3 Specificity/Selectivity 167 7.4 Response (Calibration Model) 175 7.5 Detection and Quantitation Limits 193 Acknowledgments 205 References 206 Part III Method Design and Understanding 217 8 ICHQ14 Analytical Procedure Development 219Phil Borman (GSK), Peter Hamilton (AZ), and Jean-François Dierick (GSK) 8.1 Introduction 219 8.2 The ATP 220 8.3 Connection Between Product and Analytical Procedure Understanding 222 8.4 Prior and Platform Knowledge 223 8.5 Robustness and Method Operable Design Region (MODR) 226 8.6 Link and Impact with Analytical Procedure Validation 227 8.7 Analytical Procedure Control Strategy and Ongoing Procedure Performance Verification 228 8.8 Lifecycle Strategy Including Enhanced Approaches in Submission 229 8.9 Summary 232 References 233 9 Method Selection, Development, and Optimization 237Melissa Hanna-Brown, Roman Szucs, and Brent Harrington 9.1 Introduction 237 9.2 Method Selection 239 9.3 Method Development 240 9.4 Method Optimization 251 Acknowledgments 262 References 262 10 Multivariate Analytical Procedures 265Wei Meng and Phil Borman 10.1 Introduction 265 10.2 Sampling and Data Quality 269 10.3 Development of Multivariate Models 271 10.4 Model Optimization and Validation 286 10.5 Model Maintenance and Lifecycle Management 289 10.6 Summary 293 Acknowledgments 293 References 293 11 Case Study: Robustness Investigations 301Gerd Kleinschmidt and Birgit Niederhaus 11.1 Introduction 301 11.2 General Considerations in the Context of Robustness Testing 302 11.3 Examples of Computer-Assisted Robustness Studies 304 Acknowledgment 337 References 337 12 Risk Assessment and Analytical Procedure Control Strategy 343Phil Nethercote 12.1 Background 343 12.2 Risk Management Process 343 12.3 ICH Q9 344 12.4 Using Risk Management to Develop a Control Strategy 345 12.5 Analytical Procedure Control Strategy 349 References 349 Part IV Method Performance Qualification 351 13 ICH Q2(R2): Validation of Analytical Procedures 353Joachim Ermer 13.1 How to Read This Chapter 354 13.2 Introduction 354 13.3 General Considerations for Analytical Procedure Validation 354 13.4 Validation Tests, Methodology, and Evaluation 359 13.5 Annex 2: Illustrative Examples for Analytical Techniques 367 13.6 Conclusion 370 References 371 14 Case Study: Validation of a High-performance Liquid Chromatography (HPLC) Method for Identity, Assay, and Degradation of Products 373Gerd Kleinschmidt and Birgit Niederhaus 14.1 Introduction 373 14.2 Experimental 375 14.3 Validation Summary 377 14.4 Validation Methodology 380 14.5 Conclusion 389 References 390 15 Case Study: Design and Qualification of a Delivered Dose Uniformity Procedure for a Pressurized Metered Dose Inhaler with a Focus on Sample Preparation 391Andy Rignall 15.1 Introduction 391 15.2 Designing a DDU Procedure that will Meet an ATP 392 15.3 Performance Characteristics of the DDU Procedure 401 15.4 Qualification of the DDU Procedure 402 15.5 Summary of the Analytical Procedure Control Strategy for a DDU Procedure 402 Acknowledgments 403 References 403 16 Case Study: Validation of a Bioassay Method 405Andrea Sobjak 16.1 Introduction 405 16.2 Material Considerations 407 16.3 Study Design 407 16.4 Specificity/Selectivity 410 16.5 Accuracy 411 16.6 Precision 412 16.7 Range 415 16.8 Robustness 416 16.9 Conclusion 417 Acknowledgments 417 References 418 17 Implementation of Compendial/Pharmacopeia Test Procedures 419Pauline L. McGregor 17.1 Background of Pharmacopeia Procedures 419 17.2 How Pharmacopeia Methods Are Generated and Published 420 17.3 Challenges with Compendial Procedures and the Need to Verify 420 17.4 Using Pharmacopeia Procedures in a Laboratory for the First Time 421 17.5 Verification of Pharmacopeia Procedures 422 17.6 Integration of the Verification Process and the Lifecycle Approach 423 17.7 Implementation of a Pharmacopeia Procedure Using the Lifecycle Approach 424 17.8 Performance Qualification 431 17.9 Conclusion 432 References 432 18 Transfer of Analytical Procedures 435Christophe Agut, Marion Berger, and Hugo Zuin 18.1 Transfer Process and Strategy 435 18.2 Comparative Testing 445 References 468 19 Lifecycle Approach to Transfer of Analytical Procedures 471Joachim Ermer 19.1 Facilitation of Transfer by Risk Assessment 472 19.2 Facilitation of Transfer by the APCS 472 19.3 "Lean" Transfer Strategy 473 19.4 Conclusion 474 References 475 Part V Ongoing Method Performance Verification 477 20 Continuous Improvements, Adjustments, and Changes 479Dr. Phil W. Nethercote 20.1 Drivers for Change 479 20.2 Control of Change in the Pharmaceutical Industry 480 20.3 Implementing a Change 483 References 484 21 Monitoring of Analytical Performance 487Joachim Ermer 21.1 Sources of Performance Data and Information 488 21.2 Systematic Monitoring Program 493 21.3 Analytical Performance Evaluation Tools 495 21.4 Assessment of Analytical Performance 503 21.5 Conclusion 508 References 508 Index 511