Analytical Similarity Assessment in Biosimilar Product Development

 
 
Chapman and Hall (Verlag)
  • erschienen am 3. September 2018
  • |
  • 354 Seiten
 
E-Book | PDF mit Adobe DRM | Systemvoraussetzungen
978-1-351-33946-9 (ISBN)
 

This book focuses on analytical similarity assessment in biosimilar product development following the FDA's recommended stepwise approach for obtaining totality-of-the-evidence for approval of biosimilar products. It covers concepts such as the tiered approach for assessment of similarity of critical quality attributes in the manufacturing process of biosimilar products, models/methods like the statistical model for classification of critical quality attributes, equivalence tests for critical quality attributes in Tier 1 and the corresponding sample size requirements, current issues, and recent developments in analytical similarity assessment.

  • Englisch
  • Milton
  • |
  • Großbritannien
Taylor & Francis Ltd
  • Für höhere Schule und Studium
70 schwarz-weiße Tabellen
978-1-351-33946-9 (9781351339469)
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Author

Shein-Chung Chow, Ph.D, is currently an Associate Director at Office of

Biostatistics, Center for Drug Evaluation and Research, United States Food

and Drug Administration (FDA). Prior to joining FDA, Dr. Chow was a

Professor at Duke University School of Medicine, Durham, NC. He was

also a special government employee (SGE) appointed by the FDA as an

Advisory Committee member and statistical advisor to the FDA. Prior to

that, Dr. Chow also held various positions in the pharmaceutical industry

such as Vice President at Millennium, Cambridge, MA, Executive Director at

Covance, Princeton, NJ, and Director and Department Head at Bristol-Myers

Squibb, Plainsboro, NJ. Dr. Chow is the Editor-in-Chief of the Journal of

Biopharmaceutical Statistics and the Editor-in-Chief of the Biostatistics Book Series

at Chapman and Hall/CRC Press, Taylor & Francis Group. He was elected

Fellow of the American Statistical Association and an elected member of the

ISI (International Statistical Institute). Dr. Chow is the author or co-author of

over 300 methodology papers and 29 books including Designs and Analysis

of Bioavailability and Bioequivalence Studies, Sample Size Calculations in Clinical

Research, Adaptive Design Methods in Clinical Trials, Translational Medicine,

Design and Analysis of Clinical Trials, and Quantitative Methods for Traditional

Chinese Medicine Development.

  • Cover
  • Half Title
  • Title Page
  • Copyright Page
  • Table of Contents
  • Preface
  • Author
  • Chapter 1: Introduction
  • 1.1 Background
  • 1.2 Past Experience for In Vitro Bioequivalence Testing
  • 1.2.1 Study Design and Data Collection
  • Emitted dose uniformity, priming, priming/re-priming, and tail-off profile
  • Spray pattern
  • Droplet size distribution
  • Plume geometry
  • 1.2.2 Bioequivalence Limit
  • 1.2.3 Statistical Methods
  • Non-comparative analysis
  • Non-profile Analysis
  • Profile Analysis
  • 1.2.4 Sample Size Requirement
  • 1.3 Analytical Similarity Assessment
  • 1.3.1 Tier 1 Equivalence Test
  • 1.3.2 Tier 2 Quality Range Approach
  • 1.3.3 Tier 3 Raw Data and Graphical Comparison
  • 1.4 Scientific Factors and Practical Issues
  • 1.4.1 Fundamental Similarity Assumption
  • 1.4.2 Primary Assumptions for Tiered Approach
  • 1.4.3 Fixed Approach for Margin Selection
  • 1.4.4 Inconsistent Test Results between Tiered Approaches
  • 1.4.5 Sample Size Requirement
  • 1.4.6 Relationship between Similarity Limit and Variability
  • 1.4.7 Regulator's Current Thinking on Scientific Input
  • 1.4.8 A Proposed Unified Tiered Approach
  • 1.4.9 Practical Issues
  • How Similar is Similar?
  • Criteria for biosimilarity
  • Criteria for interchangeability
  • Bridging studies for assessing biosimilarity
  • 1.4.10 Remarks
  • 1.5 Aim and Scope of the Book
  • Chapter 2: Regulatory Approval Pathway of Biosimilar Products
  • 2.1 Introduction
  • 2.2 Regulatory Requirements
  • 2.2.1 World Health Organization (WHO)
  • 2.2.2 European Union (EU)
  • 2.2.3 North America (United States of America and Canada)
  • 2.2.4 Asian Pacific Region (Japan, South Korea, and China)
  • 2.2.5 Debatable Issues in Regulatory Requirements
  • 2.3 Analytical Studies for Structural/Functional Characteristics
  • 2.4 Global Harmonization
  • 2.5 Conclusion Remarks
  • Chapter 3: CMC Requirements for Biological Products
  • 3.1 Introduction
  • 3.2 CMC Development
  • 3.2.1 Fermentation and Purification Process
  • 3.2.2 Drug Substance and Product Characterization
  • 3.2.3 Reference Standards and Container Closure System
  • 3.2.4 Practical Issues
  • 3.3 Manufacturing Process Validation
  • 3.3.1 Manufacturing Process
  • 3.3.2 Process Validation
  • 3.3.3 Practical Issues
  • 3.4 Quality Control and Assurance
  • 3.4.1 General Principles
  • 3.4.2 Quality by Design
  • 3.5 Stability Analysis
  • 3.6 Concluding Remarks
  • Chapter 4: Analytical Method Validation
  • 4.1 Introduction
  • 4.2 Regulatory Requirements
  • 4.2.1 FDA Guidance on Analytical Procedures and Methods Validation
  • 4.2.2 ICH Guidance on Assay Validation
  • 4.2.3 United States Pharmacopeia and National Formulary (USP/NF)
  • 4.3 Analytical Method Validation
  • 4.3.1 Validation Performance Characteristics
  • 4.3.2 Study Design
  • 4.3.3 Choice of Validation Performance Characteristics
  • 4.3.4 Acceptance Criteria
  • 4.4 Analysis of Validation Data
  • 4.4.1 Assessment of Accuracy, Linearity, and Specificity
  • 4.4.2 The Assessment of Assay Parameters Related to Variability
  • 4.5 Evaluation of Reliability, Repeatability, and Reproducibility
  • 4.5.1 Study Design and Statistical Model
  • 4.5.2 Variability Monitoring
  • 4.5.3 Sample Size for Comparing Variabilities
  • 4.5.4 An Example
  • 4.6 Concluding Remarks
  • Chapter 5: Critical Quality Attributes
  • 5.1 Background
  • 5.2 Identification of CQAs
  • 5.2.1 Link between CQAs and Clinical Outcomes
  • 5.2.2 Statistical Design and Methods
  • 5.3 Stepwise Approach for Demonstrating Biosimilarity
  • 5.4 Tier Assignment for Critical Quality Attributes
  • 5.4.1 Criticality or Risk Ranking
  • 5.4.2 Statistical Model
  • An Example - For the two measures proposed in the Section 5.3.2, p1 is based on the absolute difference between y and y. To test the hypothesis H0: p1 = p0 versus Ha: p1 > p0 or the given a, p0, the set of data (xi, yi) and the selected observation (x0, y
  • 5.4.3 Validity of the Translational Model
  • 5.4.4 Two-Way Translational Process
  • An Example - Using the data set given in Table 5.2, we set up the regression model x = ?0 + ?1y + e with y as the independent variable and x as the dependent variable. The estimates of the model parameters are y0 = 0.468, y1 = 0.519, and Based on this mo
  • 5.4.5 Remarks
  • 5.5 Concluding Remarks
  • Chapter 6: FDA Tiered Approach for Analytical Similarity Assessment
  • 6.1 Background
  • 6.2 Stepwise Approach for Demonstrating Biosimilarity
  • 6.3 Tier 1 Equivalence Test
  • 6.4 Other Tiered Approaches
  • 6.4.1 Quality Range Approach for Tier 2
  • 6.4.2 Raw Data and Graphical Comparison for Tier 3
  • 6.5 Some Practical Considerations
  • 6.6 Concluding Remarks
  • Chapter 7: Sample Size Requirement
  • 7.1 Introduction
  • 7.2 Traditional Approach
  • 7.2.1 Power Calculation
  • 7.2.2 Alternative Criteria for Sample Size Calculation
  • 7.3 FDA's Current Thinking and Recommendation
  • 7.3.1 FDA's Current Thinking
  • 7.3.2 FDA's Recommendation
  • 7.4 Sample Size Requirement
  • 7.4.1 Chow et al.'s Proposal for Test/Reference Lots Selection
  • 7.4.2 Recent Development
  • 7.5 Numerical Studies
  • 7.6 Concluding Remarks
  • Appendix
  • SAS Codes
  • Chapter 8: Analytical Studies with Multiple References
  • 8.1 Background
  • 8.2 Method of Pairwise Comparisons
  • 8.2.1 Equivalence Test for Tier 1 CQAs
  • 8.2.2 Pairwise Comparisons with Multiple References
  • 8.2.3 An Example
  • 8.3 Simultaneous Confidence Approach
  • 8.3.1 Assumptions and Statistical Framework
  • 8.3.2 Simultaneous Confidence Interval with the Assumption That
  • 8.3.3 Simultaneous Confidence Interval without the Assumption of
  • 8.3.4 An Example
  • 8.4 Reference Product Change
  • 8.4.1 Kang and Chow's Approach
  • 8.4.2 Criteria for Biosimilarity
  • 8.4.3 Statistical Tests for Biosimilarity
  • 8.4.4 Remarks
  • 8.5 Concluding Remarks
  • Chapter 9: Extrapolation across Indications
  • 9.1 Introduction
  • 9.2 An Example
  • 9.3 Development of Sensitivity Index
  • 9.4 Assessment of Sensitivity Index
  • 9.4.1 The Case Where e Is Random and C Is Fixed
  • 9.4.2 The Case Where e Is Fixed and C Is Random
  • 9.4.3 The Case Where Both e and C Are Random
  • 9.5 Statistical Inference of Extrapolation
  • 9.5.1 The Case Where e Is Random and C Is Fixed
  • 9.5.2 The Case Where e Is Fixed and C Is Random
  • 9.5.3 The Case Where e and C Are Random
  • 9.5.4 The Confidence Interval of the Effect Size in Original Population
  • 9.5.5 An Example
  • 9.6 Concluding Remarks
  • Appendix
  • Chapter 10: Case Studies - Recent FDA Biosimilar Submissions
  • 10.1 FDA Abbreviated Licensure Pathway
  • 10.2 Sponsor's Strategy for Regulatory Submission
  • 10.3 Avastin Biosimilar Regulatory Submission
  • 10.4 Herceptin Biosimilar
  • 10.5 Concluding Remarks
  • Chapter 11: Practical and Challenging Issues
  • 11.1 Introduction
  • 11.2 Hypotheses Testing versus Confidence Interval Approach
  • 11.2.1 Interval Hypotheses Testing
  • 11.2.2 Confidence Interval Approach
  • 11.2.3 Remarks
  • 11.3 Totality-of-the-Evidence
  • 11.3.1 Primary Assumptions of Stepwise Approach
  • 11.3.2 Relationships among Analytical, PK/PD, and Clinical Similarity
  • 11.3.3 Practical Issues
  • 11.3.4 Examples
  • 11.3.5 Remarks
  • 11.4 Inconsistencies between Tiered Approaches
  • 11.4.1 In Vitro Bioequivalence Testing versus Analytical Testing
  • 11.4.2 Primary Assumptions for Tiered Approach
  • 11.4.3 Inconsistencies between Different Tiered Tests
  • 11.5 Individual Bioequivalence
  • 11.6 Commonly Asked Questions from the Sponsors
  • 11.7 Concluding Remarks
  • Chapter 12: Recent Development
  • 12.1 Introduction
  • 12.2 Comparing Means versus Comparing Variances
  • 12.2.1 Generally Similar versus Highly Similar
  • 12.2.2 Similarity Test in Variability
  • 12.2.3 Remarks
  • 12.3 Switching Design
  • 12.3.1 Introduction
  • 12.3.2 Concept and Criteria for Drug Interchangeability
  • 12.3.3 Hybrid Parallel-Crossover Design
  • 12.3.4 Statistical Model and Analysis
  • 12.3.5 Sample Size Requirement
  • 12.4 Non-Medical Switching
  • 12.4.1 Introduction
  • 12.4.2 Approaches for Evaluation of Non-Medical Switch
  • 12.4.3 Clinical Studies
  • 12.4.4 Scientific Factors and Statistical Considerations
  • 12.4.4.1 Scientific Factors
  • 12.4.4.2 Statistical Considerations
  • 12.4.5 Design and Analysis of Switching Studies
  • 12.5 FDA Draft Guidance on Analytical Similarity Assessment
  • 12.6 Concluding Remarks
  • References and Further Reading
  • Index

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