Method Validation in Pharmaceutical Analysis

Joachim Ermer is Head of Quality Control Services Chemistry at Sanofi in Frankfurt, Germany, and Global Reference Standards Coordinator of Sanofi. He studied biochemistry at University of Halle, Germany, and obtained a PhD in enzyme kinetics in 1988. He has more than 20 years of experience in pharmaceutical analytics including development projects, global responsibilities as Director of Analytical Processes and Technology, and Head of Quality Control. He is member of the USP Expert Panel on Validation and Verification, of the EFPIA Quality by Design Working Group, and of the Focus Group Analytics and Quality Assurance of the International Association of Pharmaceutical Technology (APV). From 2000 till 2008, he was Deputy Head of the Working Group Quality Control / Pharmaceutical Analytics of the German Pharmaceutical Society (DPhG). His special interest has been focused early on analytical validation and related topics, such as performance evaluation, statistics, and transfer of analytical procedures.. Phil Nethercote is the Analytical Head and API Analytical Lead for the Global Manufacturing and Supply division of GSK. He has a degree in chemistry from Herriot Watt University in Edinburgh and obtained a PhD in HPLC retention mechanisms from the University of Stirling in 1987. He is a Chartered Chemist and a member of the Royal Society of Chemistry. He has over 25 years of experience in the pharmaceutical industry the majority of which has been with Glaxo, Glaxo Wellcome and GSK where he has led analytical development and new product introduction teams in the UK and in Singapore. In his current role he provides leadership for analytical systems, processes and standards across GSKs global network of manufacturing sites. He is member of the USP Expert Panel on Validation and Verification, of the EFPIA Analytical Quality by Design Working Group and led the revision of the analytical section of the second edition of the ISPE technology transfer guide He has a passion for ensuring efforts invested in Analytical Method Validation and Transfer add real value in ensuring the methods produce fit for purpose data and has been a strong advocate in applying QbD principles to help achieve that aim.

• Foreword xiiiList of Contributors xv1 Analytical Validation within the Pharmaceutical Lifecycle 1Phil Nethercote and Joachim Ermer1.1 Development of Process and Analytical Validation Concepts 11.2 Alignment between Process and Analytics: Three-Stage Approach 41.3 Predefined Objectives: Analytical Target Profile 51.4 Analytical Life Cycle 8References 92 Analytical Instrument Qualification 112.1 Analytical Instrument and System Qualification 11Christopher Burgess and R. D. McDowall2.1.1 Data Quality and Integrity in a GMP Environment 112.1.1.1 Criteria for Quality Data 112.1.1.2 Regulatory Rationale for Qualified Analytical Instruments 122.1.2 USP General Chapter <1058> 122.1.2.1 Data Quality Triangle 142.1.2.2 Analytical Instrument Qualification Life Cycle: the Four Qs Model 142.1.2.3 Risk-Based Classification of Apparatus, Instruments, and Systems 152.1.2.4 Roles and Responsibilities for AIQ 172.1.2.5 Software Validation for Group B and C Systems 182.1.3 Enhancement of <1058> and Harmonization of a Risk-Based Approach to Instruments and Systems with GAMP Laboratory GPG Second Edition 182.1.3.1 Increased Granularity of USP <1058> Groups 182.1.3.2 Clarification of AIQ Terminology 192.1.3.3 A Continuum of Analytical Apparatus, Instruments, and Systems 192.1.3.4 Mapping USP <1058> Instrument Groups to GAMP Software Categories 202.1.3.5 Enhanced Data Quality Triangle 202.1.4 Risk-Based Approaches to Analytical Instrument and System Qualification 202.1.4.1 Expanded <1058> Instrument and System Categories 232.2 Efficient and Economic HPLC Performance Qualification 25Hermann Wätzig2.2.1 Introduction 252.2.1.1 The Importance of Analytical Instrument Qualification 252.2.1.2 Terms and Definitions 252.2.1.3 Continuous Performance Qualification: More by Less 272.2.2 Development of the Revised OQ/PQ Parameters List 272.2.3 Transfer of Modular Parameters into the Holistic Approach 292.2.3.1 Autosampler 292.2.3.2 Solvent Delivery System 292.2.3.3 Detector 302.2.4 OQ/PQ Data in Comparison with SST Data 322.2.5 Control Charts 332.2.6 General Procedure for Continuous PQ 342.2.7 Concluding Remarks 36Acknowledgment 37Abbreviations 37References 383 Establishment of Measurement Requirements – Analytical Target Profile and Decision Rules 41Mary Lee Jane Weitzel3.1 Introduction 413.2 Defining the Fitness for Intended Use 423.3 Decision Rules 423.4 Overview of Process to Develop Requirements for Procedure Performance 433.5 Decision Rules and Compliance 433.6 Calculating Target Measurement Uncertainty 453.6.1 Coverage Factor, k, and Data Distributions 463.7 Types of Decision Rules 473.7.1 Decision Rules That Use Guard Bands 483.8 Target Measurement Uncertainty in the Analytical Target Profile 493.8.1 Cost of Analysis 493.9 Bias and Uncertainty in a Procedure 503.10 ATP and Key Performance Indicators 513.11 Measurement Uncertainty 513.11.1 What Uncertainty Is 513.11.2 Reporting Measurement Uncertainty 523.11.3 How Uncertainty is Estimated 543.11.4 Uncertainty Contains All Sources of Random Variability 553.12 Example 563.13 Conclusion 57References 584 Establishment of Measurement Requirements – Performance-Based Specifications 59Todd L. Cecil4.1 Introduction 594.2 Intended Purpose 604.3 Identification 604.4 Assay 624.4.1 Precision 624.4.2 Accuracy 634.4.3 Precision and Accuracy 644.4.3.1 Relationship between Accuracy and Precision 644.4.4 Specificity 654.4.4.1 Chromatographic Procedures 654.4.4.2 Non-chromatographic Procedures 664.4.5 Linearity and Range 674.4.5.1 Linearity 674.4.5.2 Range 674.5 Impurities 684.6 Limit Tests 694.6.1 Limit of Detection 694.6.2 Precision 704.6.3 Specificity 704.7 Quantitative Tests 704.7.1 Accuracy 704.7.2 Precision 714.7.3 Specificity and Range 714.8 Summary 71References 715 Method Performance Characteristics 73Joachim Ermer5.1 Introduction 735.2 Precision 745.2.1 Distribution of Data 745.2.1.1 The Normal Distribution and its Parameters 745.2.1.2 Robust Parameter 845.2.2 Precision Levels 845.2.2.1 System or Instrument Precision 855.2.2.2 Repeatability 865.2.2.3 Intermediate Precision and Reproducibility 865.2.3 Calculation of Precisions and Variances 895.2.3.1 Analysis of Variances (ANOVA) 905.2.3.2 Calculation of Precision from Linear Regression 925.2.4 Concentration Dependency of Precision 935.2.5 Precision Acceptance Criteria 955.2.5.1 Precision of the Reportable Result 955.2.5.2 Optimization of the Calibration Format 975.2.5.3 Acceptable Precision for Assay 1015.2.5.4 Acceptable Precision for Impurities and Minor Components 1055.2.6 Precisions Benchmarks 1075.2.6.1 Precisions for LC Assay 1085.2.7 Sources to Obtain and Supplement Precisions 1165.2.7.1 Precisions from Stability 1175.2.8 Precision Highlights 1195.3 Accuracy and Range 1195.3.1 Drug Substance 1225.3.1.1 Significance Tests 1225.3.1.2 Equivalence Tests 1245.3.1.3 Direct Comparison 1255.3.1.4 Comparison Examples 1255.3.2 Drug Product 1265.3.2.1 Percentage Recovery 1275.3.2.2 Recovery Function 1285.3.2.3 Standard Addition 1285.3.2.4 Accuracy of Drug Product by Comparison 1295.3.3 Impurities/Degradants 1295.3.3.1 Recovery of Spiked Impurities 1295.3.3.2 Accuracy of the Integration Mode 1305.3.3.3 Response Factors 1315.3.4 Acceptance Criteria (ATP Requirements) 1325.3.4.1 Can this Theoretically Obtained Relationship be Supported by Experimental Results? 1355.3.5 Joint Evaluation of Accuracy and Precision 1365.3.6 Accuracy Highlights 1375.4 Specificity 1375.4.1 Demonstration of Specificity by Accuracy 1405.4.2 Chromatographic Resolution 1405.4.3 Peak Purity (Co-elution) 1415.4.3.1 Rechromatography 1415.4.3.2 Diode Array Detection 1425.4.3.3 Lc-ms 1435.4.4 Specificity Highlights 1455.5 Linearity 1455.5.1 Unweighted Linear Regression 1475.5.1.1 Graphical Evaluation of Linearity 1515.5.1.2 Numerical Regression Parameters 1535.5.1.3 Statistical Linearity Tests 1555.5.1.4 Evaluation of the Intercept (Absence of Systematic Errors) 1585.5.2 Weighted Linear Regression 1605.5.3 Appropriate Calibration Models 1625.5.4 Nonlinear and Other Regression Techniques 1625.5.5 Linearity Highlights 1635.6 Detection and Quantitation Limit 1645.6.1 Requirements in Pharmaceutical Impurity Determination 1645.6.1.1 Intermediate Quantitation Limit 1665.6.1.2 General Quantitation Limit 1665.6.2 Approaches Based on the Blank 1675.6.3 Determination of DL/QL from Linearity 1675.6.3.1 Standard Deviation of the Response 1695.6.3.2 95% Prediction Interval of the Regression Line 1715.6.3.3 Aproach Based on German Standard DIN 32645 1725.6.3.4 From the Relative Uncertainty 1735.6.4 Precision Based Approaches 1745.6.5 Comparison of the Various Approaches 1755.6.6 Quantitation Limit Highlights 1765.7 Glossary 177Acknowledgments 182References 1826 Method Design and Understanding 1916.1 Method Selection, Development, and Optimization 191Melissa Hanna-Brown, Roman Szucs, and Brent Harrington6.1.1 Introduction 1916.1.2 Method Selection 1926.1.3 Method Development 1946.1.4 Method Optimization 205Acknowledgments 2176.2 Analytical Quality by Design and Robustness Investigations 217Rosario LoBrutto6.2.1 Introduction 2176.2.2 Method Validation Requirements 2206.2.3 Robustness 2216.2.4 Analytical Quality by Design 2236.2.5 Design of Experiments (DOE) 2256.2.6 FMEA (Failure Mode Effect Analysis) 2276.2.7 Illustrative Case Study 2316.2.8 Illustrative Example for Statistical Analysis 2346.2.9 Control Strategy 2396.2.10 Conclusions 240Acknowledgments 2416.3 Case Study: Robustness Investigations 241Gerd Kleinschmidt6.3.1 Introduction 2416.3.2 General Considerations in the Context of Robustness Testing 2426.3.2.1 Basic and Intrinsic Parameters 2436.3.3 Examples of Computer-Assisted Robustness Studies 2456.3.3.1 Robustness Testing Based on Chromatography Modeling Software 2466.3.3.2 Robustness Testing Based on Experimental Design 258Acknowledgments 2876.4 System Suitability Tests 287Joachim Ermer6.4.1 Chromatographic System Suitability Parameters 2886.4.1.1 Signal-to-Noise Ratio 2896.4.1.2 Test for Required Detectability 2916.4.1.3 Injection Precision 2926.4.1.4 System Precision for Impurities? 2936.4.2 Non-chromatographic System Suitability Parameters 2936.4.3 Design of System Suitability Tests 294References 2957 Method Performance Qualification 3037.1 Introduction 303Joachim Ermer7.1.1 Example of a Precision Study 3057.2 CaseStudy:QualificationofanHPLCMethodforIdentity,Assay, and Degradation Products 308Gerd Kleinschmidt7.2.1 Introduction 3087.2.2 Experimental 3107.2.3 Qualification Summary 3107.2.4 Qualification Methodology 3147.2.4.1 Specificity 3147.2.4.2 Linearity 3147.2.4.3 Accuracy 3187.2.4.4 Precision 3207.2.4.5 Quantitation Limit 3217.2.4.6 Range 3237.2.5 Conclusion 3247.3 Design and Qualification of a Delivered Dose Uniformity Procedure for a Pressurized Metered Dose Inhaler 324Andy Rignall7.3.1 Introduction 3247.3.1.1 Analytical Procedures for Complex Dosage Forms 3247.3.1.2 Human and Environmental Factors Associated with Complex Laboratory Procedures 3257.3.1.3 Delivered Dose Uniformity Testing for Inhalation Products 3257.3.2 Designing a Delivered Dose Uniformity Procedure that will Meet an Atp 3267.3.2.1 Risk Assessment and Classification 3277.3.2.2 Noise Factors Associated with Dose Collection 3317.3.2.3 Dose Recovery and Sample Preparation 3337.3.2.4 Automated Delivered Dose Uniformity Procedure 3337.3.2.5 Results Calculation and Reporting 3347.3.3 Performance Characteristics of the Delivered Dose Uniformity Procedure 3347.3.4 Qualification of the Delivered Dose Uniformity Procedure 3357.3.5 Summary of the Analytical Control Strategy for a Delivered Dose Uniformity Procedure 336Acknowledgment 3377.4 Implementation of Compendial/Pharmacopeia Test Procedures 337Pauline McGregor7.4.1 Background of Pharmacopeia Procedures 3377.4.2 How Pharmacopeia Methods are Generated and Published 3387.4.3 Challenges with Compendial Procedures and the Need to Verify 3387.4.4 Using Pharmacopeia Procedures in a Laboratory for the First Time 3397.4.5 Current Approach to Verification of Pharmacopeia Procedures 3397.4.6 Integration of the Current Verification Process and the Lifecycle Approach 3407.4.7 Implementation of a Pharmacopeia Procedure Using the Lifecycle Approach 3417.4.7.1 Gather Knowledge 3417.4.7.2 Finalizing the ATP 3467.4.8 Performance Qualification 3477.4.9 Conclusion 3487.5 Transfer of Analytical Procedures 348Christophe Agut and Joachim Ermer7.5.1 Transfer Process and Strategy 3497.5.1.1 Regulatory and International Guidance 3497.5.1.2 Transfer Process 3507.5.2 Comparative Testing 3557.5.2.1 Equivalence-Based Methodology 3557.5.2.2 Direct Comparison 369Acknowledgments 372References 3728 Continued Method Performance Verification 377Phil Nethercote and Christopher Burgess8.1 Introduction 3778.2 Routine Monitoring 3778.2.1 Introduction 3778.2.2 Establishing a Control Chart 3808.2.3 Examples of Application of Control Charting to Analytical Procedures 3828.2.3.1 Example 1 3828.2.3.2 Example 2 3828.2.4 Periodic Review 3838.2.5 Determination of Root Cause Using CuSum Analysis 3858.3 Investigating and Addressing Aberrant Data 3918.3.1 Laboratory Failure Investigation 3918.3.2 Classification of Atypical or Aberrant Results 3938.3.3 Statistical Outlier Tests for Out-of-Expectation Results 3998.3.4 Summary 4058.4 Continual Improvement 4068.4.1 Introduction 4068.4.2 Control of Change 4068.4.2.1 Risk Assessment of Changes 407References 409Index 411