Method Validation in Pharmaceutical Analysis

Contents

Foreword

List of Contributors

Chapter 1 Analytical Validation within the Pharmaceutical Lifecycle

1.1 Development of Process and Analytical Validation Concepts

1.2 Alignment between Process and Analytics: Three-Stage Approach

1.3 Predefined Objectives: Analytical Target Profile

1.4 Analytical Life Cycle

References

Chapter 2 Analytical Instrument Qualification

2.1 Analytical Instrument and System Qualification

2.1.1 Data Quality and Integrity in a GMP Environment

2.1.1.1 Criteria for Quality Data

2.1.1.2 Regulatory Rationale for Qualified Analytical Instruments

2.1.2 USP General Chapter <1058>

2.1.2.1 Data Quality Triangle

2.1.2.2 Analytical Instrument Qualification Life Cycle: the Four Qs Model

2.1.2.3 Risk-Based Classification of Apparatus, Instruments, and Systems

2.1.2.4 Roles and Responsibilities for AIQ

2.1.2.5 Software Validation for Group B and C Systems

2.1.3 Enhancement of <1058> and Harmonization of a Risk-Based Approach to Instruments and Systems with GAMP Laboratory GPG Second Edition

2.1.3.1 Increased Granularity of USP <1058> Groups

2.1.3.2 Clarification of AIQ Terminology

2.1.3.3 A Continuum of Analytical Apparatus, Instruments, and Systems

2.1.3.4 Mapping USP <1058> Instrument Groups to GAMP Software Categories

2.1.3.5 Enhanced Data Quality Triangle

2.1.4 Risk-Based Approaches to Analytical Instrument and System Qualification

2.1.4.1 Expanded <1058> Instrument and System Categories

2.2 Efficient and Economic HPLC Performance Qualification

2.2.1 Introduction

2.2.1.1 The Importance of Analytical Instrument Qualification

2.2.1.2 Terms and Definitions

2.2.1.3 Continuous Performance Qualification: More by Less

2.2.2 Development of the Revised OQ/PQ Parameters List

2.2.3 Transfer of Modular Parameters into the Holistic Approach

2.2.3.1 Autosampler

2.2.3.2 Solvent Delivery System

2.2.3.3 Detector

2.2.4 OQ/PQ Data in Comparison with SST Data

2.2.5 Control Charts

2.2.6 General Procedure for Continuous PQ

2.2.7 Concluding Remarks

Acknowledgment

Abbreviations

References

Chapter 3 Establishment of Measurement Requirements - Analytical Target Profile and Decision Rules

3.1 Introduction

3.2 Defining the Fitness for Intended Use

3.3 Decision Rules

3.4 Overview of Process to Develop Requirements for Procedure Performance

3.5 Decision Rules and Compliance

3.6 Calculating Target Measurement Uncertainty

3.6.1 Coverage Factor, k, and Data Distributions

3.7 Types of Decision Rules

3.7.1 Decision Rules That Use Guard Bands

3.8 Target Measurement Uncertainty in the Analytical Target Profile

3.8.1 Cost of Analysis

3.9 Bias and Uncertainty in a Procedure

3.10 ATP and Key Performance Indicators

3.11 Measurement Uncertainty

3.11.1 What Uncertainty Is

3.11.2 Reporting Measurement Uncertainty

3.11.3 How Uncertainty is Estimated

3.11.4 Uncertainty Contains All Sources of Random Variability

3.12 Example

3.13 Conclusion

References

Chapter 4 Establishment of Measurement Requirements - Performance-Based Specifications

4.1 Introduction

4.2 Intended Purpose

4.3 Identification

4.4 Assay

4.4.1 Precision

4.4.2 Accuracy

4.4.3 Precision and Accuracy

4.4.3.1 Relationship between Accuracy and Precision

4.4.4 Specificity

4.4.4.1 Chromatographic Procedures

4.4.4.2 Non-chromatographic Procedures

4.4.5 Linearity and Range

4.4.5.1 Linearity

4.4.5.2 Range

4.5 Impurities

4.6 Limit Tests

4.6.1 Limit of Detection

4.6.2 Precision

4.6.3 Specificity

4.7 Quantitative Tests

4.7.1 Accuracy

4.7.2 Precision

4.7.3 Specificity and Range

4.8 Summary

References

Chapter 5 Method Performance Characteristics

5.1 Introduction

5.2 Precision

5.2.1 Distribution of Data

5.2.1.1 The Normal Distribution and its Parameters

5.2.1.2 Robust Parameter

5.2.2 Precision Levels

5.2.2.1 System or Instrument Precision

5.2.2.2 Repeatability

5.2.2.3 Intermediate Precision and Reproducibility

5.2.3 Calculation of Precisions and Variances

5.2.3.1 Analysis of Variances (ANOVA)

5.2.3.2 Calculation of Precision from Linear Regression

5.2.4 Concentration Dependency of Precision

5.2.5 Precision Acceptance Criteria

5.2.5.1 Precision of the Reportable Result

5.2.5.2 Optimization of the Calibration Format

5.2.5.3 Acceptable Precision for Assay

5.2.5.4 Acceptable Precision for Impurities and Minor Components

5.2.6 Precisions Benchmarks

5.2.6.1 Precisions for LC Assay

5.2.7 Sources to Obtain and Supplement Precisions

5.2.7.1 Precisions from Stability

5.2.8 Precision Highlights

5.3 Accuracy and Range

5.3.1 Drug Substance

5.3.1.1 Significance Tests

5.3.1.2 Equivalence Tests

5.3.1.3 Direct Comparison

5.3.1.4 Comparison Examples

5.3.2 Drug Product

5.3.2.1 Percentage Recovery

5.3.2.2 Recovery Function

5.3.2.3 Standard Addition

5.3.2.4 Accuracy of Drug Product by Comparison

5.3.3 Impurities/Degradants

5.3.3.1 Recovery of Spiked Impurities

5.3.3.2 Accuracy of the Integration Mode

5.3.3.3 Response Factors

5.3.4 Acceptance Criteria (ATP Requirements)

5.3.4.1 Can this Theoretically Obtained Relationship be Supported by Experimental Results?

5.3.5 Joint Evaluation of Accuracy and Precision

5.3.6 Accuracy Highlights

5.4 Specificity

5.4.1 Demonstration of Specificity by Accuracy

5.4.2 Chromatographic Resolution

5.4.3 Peak Purity (Co-elution)

5.4.3.1 Rechromatography

5.4.3.2 Diode Array Detection

5.4.3.3 LC-MS

5.4.4 Specificity Highlights

5.5 Linearity

5.5.1 Unweighted Linear Regression

5.5.1.1 Graphical Evaluation of Linearity

5.5.1.2 Numerical Regression Parameters

5.5.1.3 Statistical Linearity Tests

5.5.1.4 Evaluation of the Intercept (Absence of Systematic Errors)

5.5.2 Weighted Linear Regression

5.5.3 Appropriate Calibration Models

5.5.4 Nonlinear and Other Regression Techniques

5.5.5 Linearity Highlights

5.6 Detection and Quantitation Limit

5.6.1 Requirements in Pharmaceutical Impurity Determination

5.6.1.1 Intermediate Quantitation Limit

5.6.1.2 General Quantitation Limit

5.6.2 Approaches Based on the Blank

5.6.3 Determination of DL/QL from Linearity

5.6.3.1 Standard Deviation of the Response

5.6.3.2 95% Prediction Interval of the Regression Line

5.6.3.3 Aproach Based on German Standard DIN 32645

5.6.3.4 From the Relative Uncertainty

5.6.4 Precision Based Approaches

5.6.5 Comparison of the Various Approaches

5.6.6 Quantitation Limit Highlights

5.7 Glossary

Acknowledgments

References

Chapter 6 Method Design and Understanding

6.1 Method Selection, Development, and Optimization

6.1.1 Introduction

6.1.2 Method Selection

6.1.3 Method Development

6.1.4 Method Optimization

Acknowledgments

6.2 Analytical Quality by Design and Robustness Investigations

6.2.1 Introduction

6.2.2 Method Validation Requirements

6.2.3 Robustness

6.2.4 Analytical Quality by Design

6.2.5 Design of Experiments (DOE)

6.2.6 FMEA (Failure Mode Effect Analysis)

6.2.7 Illustrative Case Study

6.2.8 Illustrative Example for Statistical Analysis

6.2.9 Control Strategy

6.2.10 Conclusions

Acknowledgments

6.3 Case Study: Robustness Investigations

6.3.1 Introduction

6.3.2 General Considerations in the Context of Robustness Testing

6.3.2.1 Basic and Intrinsic Parameters

6.3.3 Examples of Computer-Assisted Robustness Studies

6.3.3.1 Robustness Testing Based on Chromatography Modeling Software

6.3.3.2 Robustness Testing Based on Experimental Design

Acknowledgments

6.4 System Suitability Tests

6.4.1 Chromatographic System Suitability Parameters

6.4.1.1 Signal-to-Noise Ratio

6.4.1.2 Test for Required Detectability

6.4.1.3 Injection Precision

6.4.1.4 System Precision for Impurities?

6.4.2 Non-chromatographic System Suitability Parameters

6.4.3 Design of System Suitability Tests

References

Chapter 7 Method Performance Qualification

7.1 Introduction

7.1.1 Example of a Precision Study

7.2 Case Study: Qualification of an HPLC Method for Identity, Assay, and Degradation Products

7.2.1 Introduction

7.2.2 Experimental

7.2.3 Qualification Summary

7.2.4 Qualification Methodology

7.2.4.1 Specificity

7.2.4.2 Linearity

7.2.4.3 Accuracy

7.2.4.4 Precision

7.2.4.5 Quantitation Limit

7.2.4.6 Range

7.2.5 Conclusion

7.3 Design and Qualification of a Delivered Dose Uniformity Procedure for a Pressurized Metered Dose Inhaler

7.3.1 Introduction

7.3.1.1 Analytical Procedures for Complex Dosage Forms

7.3.1.2 Human and Environmental Factors Associated with Complex Laboratory Procedures

7.3.1.3 Delivered Dose Uniformity Testing for Inhalation Products

7.3.2 Designing a Delivered Dose Uniformity Procedure that will Meet an ATP

7.3.2.1 Risk Assessment and Classification

7.3.2.2 Noise Factors Associated with Dose Collection

7.3.2.3 Dose Recovery and Sample Preparation

7.3.2.4 Automated Delivered Dose Uniformity Procedure

7.3.2.5 Results Calculation and Reporting

7.3.3 Performance Characteristics of the Delivered Dose Uniformity Procedure

7.3.4 Qualification of the Delivered Dose Uniformity Procedure

7.3.5 Summary of the Analytical Control Strategy for a Delivered Dose Uniformity Procedure

Acknowledgment

7.4 Implementation of Compendial/Pharmacopeia Test Procedures

7.4.1 Background of Pharmacopeia Procedures

7.4.2 How Pharmacopeia Methods are Generated and Published

7.4.3 Challenges with Compendial Procedures and the Need to Verify

7.4.4 Using Pharmacopeia Procedures in a Laboratory for the First Time

7.4.5 Current Approach to Verification of Pharmacopeia Procedures

7.4.6 Integration of the Current Verification Process and the Lifecycle Approach

7.4.7 Implementation of a Pharmacopeia Procedure Using the Lifecycle Approach

7.4.7.1 Gather Knowledge

7.4.7.2 Finalizing the ATP

7.4.8 Performance Qualification

7.4.9 Conclusion

7.5 Transfer of Analytical Procedures

7.5.1 Transfer Process and Strategy

7.5.1.1 Regulatory and International Guidance

7.5.1.2 Transfer Process

7.5.2 Comparative Testing

7.5.2.1 Equivalence-Based Methodology

7.5.2.2 Direct Comparison

Acknowledgments

References

Chapter 8 Continued Method Performance Verification

8.1 Introduction

8.2 Routine Monitoring

8.2.1 Introduction

8.2.2 Establishing a Control Chart

8.2.3 Examples of Application of Control Charting to Analytical Procedures

8.2.3.1 Example 1

8.2.3.2 Example 2

8.2.4 Periodic Review

8.2.5 Determination of Root Cause Using CuSum Analysis

8.3 Investigating and Addressing Aberrant Data

8.3.1 Laboratory Failure Investigation

8.3.2 Classification of Atypical or Aberrant Results

8.3.3 Statistical Outlier Tests for Out-of-Expectation Results

8.3.4 Summary

8.4 Continual Improvement

8.4.1 Introduction

8.4.2 Control of Change

8.4.2.1 Risk Assessment of Changes

References

Index

EULA