Methodologies in Biosimilar Product Development

✍ Scribed by Sang Joon Lee, Shein-Chung Chow

• Publisher: CRC Press/Chapman & Hall
• Year: 2021
• Tongue: English
• Leaves: 393
• Series: Chapman & Hall/CRC Biostatistics Series
• Category: Library

✦ Synopsis

Methodologies for Biosimilar Product Development covers the practical and challenging issues that are commonly encountered during the development, review, and approval of a proposed biosimilar product. These practical and challenging issues include, but are not limited to the mix-up use of interval hypotheses testing (i.e., the use of TOST) and confidence interval approach, a risk/benefit assessment for non-inferiority/similarity margin, PK/PD bridging studies with multiple references, the detection of possible reference product change over time, design and analysis of biosimilar switching studies, the assessment of sensitivity index for assessment of extrapolation across indications without collecting data from those indications not under study, and the feasibility and validation of non-medical switch post-approval.

Key Features:

• Reviews withdrawn draft guidance on analytical similarity assessment.
• Evaluates various methods for analytical similarity evaluation based on FDA’s current guidelines.
• Provides a general approach for the use of n-of-1 trial design for assessment of interchangeability.
• Discusses the feasibility and validity of the non-medical switch studies.
• Provides innovative thinking for detection of possible reference product change over time.

This book embraces innovative thinking of design and analysis for biosimilar studies, which are required for review and approval of biosimilar regulatory submissions.

✦ Table of Contents

Cover
Half Title
Series Page
Title Page
Copyright Page
Table of Contents
Preface
Authors
Contributors
1. Biosimilar Product Development
1.1 Introduction
1.2 Regulatory Requirements for Totality-of-the-Evidence
1.2.1 Totality-of-the-Evidence
1.2.2 Examples
1.2.3 Concluding Remarks
1.3 Practical Issues and Recent Methodology Development in Biosimilar Product Development
1.3.1 Interval Hypotheses Testing Versus the Confidence Interval Approach for Analytical Similarity Evaluation
1.3.2 Absolute Difference Versus Relative Difference
1.3.3 Statistical Methods for Analytical Similarity Evaluation
1.3.4 Current Practical Issues
1.3.4.1 Totality-of-the-Evidence
1.3.4.2 Analytical/PK Bridging Studies
1.3.4.3 Reference Product Change
1.3.4.4 Extrapolation
1.3.5 Points to Consider for Best Practice in Biosimilarity Assessment
1.3.5.1 Equivalence Test with a Flexible Margin
1.3.5.2 Modified QR (mQR) Method
1.3.5.3 Confidence Region Approach
1.3.5.4 Concluding Remarks
1.4 Aim and Scope of the Book
References
2. CMC Considerations for Quality
2.1 Introduction
2.2 CMC Development
2.3 Product Characterization and Specification
2.3.1 General Description
2.3.2 Drug Substance Characterization
2.3.3 Product Characterization
2.3.4 Practical Issues
2.4 Manufacture and Process Validation
2.4.1 Manufacturing Process
2.4.2 Process Validation
2.4.3 Commonly Encountered Issues
2.5 Quality Control and Quality Assurance
2.5.1 General Principles
2.5.2 Starting Materials
2.5.3 Seed Lot and Cell Bank System
2.5.4 Operating Principles
2.5.5 Premises and Equipment
2.5.6 Practical Issues
2.6 Reference Standards, Container Closure System, and Stability
2.6.1 Reference Standards
2.6.2 Container Closure System
2.6.3 Stability
2.7 Concluding Remarks
References
3. Quality by Design
3.1 Background
3.2 Definition of QbD
3.2.1 Benefit of QbD
3.2.2 Comparison of the Traditional Approach and the QbD Approach
3.3 Bioprocess Development
3.3.1 Upstream Process Development
3.3.2 Downstream Process
3.3.3 Analytical Development
3.4 Elements of QbD
3.4.1 QTPP
3.4.2 CQAs
3.4.3 CPP
3.4.4 Design Space
3.4.5 Control Strategy and Robustness
3.4.6 CPV
3.5 QbD tools
3.5.1 Risk Assessment
3.5.2 Design of Experiments (DoE)
3.5.2.1 Full Factorial Design
3.5.2.2 Fractional Factorial Design
3.5.2.3 Definitive Screening Design (DSD)
3.5.2.4 Plackett–Burman design
3.5.2.5 Central Composite Design
3.5.2.6 Box–Behnken Design
3.5.2.7 Optimal Design
3.5.2.8 Fraction of Design Space Plot
3.5.2.9 Analysis of Variance & Fitting a Model
3.5.2.10 Parameter Estimates
3.5.2.11 Prediction Profiler
3.5.2.12 Contour Profiler
3.5.3 Multivariate Analysis (MVA)
3.5.3.1 Method-PCA
3.5.3.2 PCA-Example
3.5.3.3 Method-PLS
3.5.3.4 PLS-Example
3.5.4 Process Analytical Technology (PAT)
3.5 Concluding Remarks
References
4. Stability Studies
4.1 Introduction
4.2 Regulatory Stability Guidance on Biologicals
4.2.1 ICH/EMA Guidelines on Stability
4.2.2 ICH Q5C Stability Guideline
4.3 Stability Indicating Profile and Expiration Dating Period
4.3.1 Stability Indicating Assay
4.3.2 Expiration Dating Period
4.4 Stability Designs
4.4.1 Basic Matrix 2/3 on Time Design
4.4.2 Matrix 2/3 on Time Design with Multiple Packages
4.4.3 Matrix 2/3 on Time Design with Multiple Packages and Multiple Strengths
4.4.4 Matrix 1/3 on Time Design
4.4.5 Matrix on Batch × Strength × Package Combinations
4.4.6 Uniform Matrix Design
4.4.7 Comparison of Designs
4.4.8 Factors Acceptable to Matrix
4.4.9 General Rules
4.5 Statistical Analysis
4.5.1 Separate Analysis Approach
4.5.2 One Analysis Approach, without Testing Poolability
4.5.3 One Analysis: Testing Poolability
4.6 Concluding Remarks
References
5. Two One-Sided Tests Versus Confidence Interval Approach
5.1 Introduction
5.2 Hypotheses Testing Versus Confidence Interval
5.2.1 Hypotheses Testing
5.2.2 CI Approach
5.2.3 Remarks
5.3 A Comparison of Hypotheses Testing and Confidence Interval Approach
5.3.1 Performance Characteristics
5.3.2 Simulation Studies
5.4 An Example – Binary Responses
5.5 Sample Size Requirement
5.6 Concluding Remarks
References
Appendix
6. Equivalence Test with Flexible Margin
6.1 Introduction
6.2 Equivalence Test with Fixed Margin
6.3 Range of EAC Margin with Flexible Index f
6.4 Equivalence Test with Flexible Margin
6.5 Sample Size Requirement
6.6 Concluding Remarks
References
7. Modified Quality Range Method for Analytical Similarity Evaluation
7.1 Introduction
7.1.1 Totality-of-Evidence
7.1.2 Limitations and Risk of the QR Method
7.2 Quality Range (QR) Method
7.2.1 Primary Assumptions
7.3 Types of mQR Methods
7.3.1 Similarity of Standard Deviations
7.3.2 Effect Size (ES) mQR
7.3.2.1 Selection of k
7.3.3 Plausibility Interval (PI) mQR
7.3.3.1 Preliminary Step 1: Plausibility Interval and Tolerance Interval of Difference
7.3.3.2 Preliminary Step 2: Similarity of Standard Deviations
7.3.3.3 Selection of a
7.4 Simulation Studies
7.4.1 Simulation Setting
7.4.2 Monte Carlo Study of the QR Approach and the Equivalence Test
7.4.3 Monte Carlo Study of the mQR Methods
7.4.3.1 A Comparison between the QR and the mQR Methods
7.4.3.2 A Comparison between the mQR Methods
7.5 Sample Size Requirements
7.5.1 Large Sample Size
7.6 Concluding Remarks
References
8. PK/PD Bridging Studies
8.1 Introduction
8.2 Issues with Multiple References
8.3 Innovative Designs with Multiple References
8.3.1 Williams Design
8.3.2 Multiple n-of-1 Trial Design
8.3.3 Remarks
8.4 Statistical Model and Analysis
8.4.1 Statistical Model
8.4.2 Statistical Methods for Biosimilarity Assessment
8.5 Sample Size Requirement
8.6 Concluding Remarks
References
9. Non-inferiority/Similarity Margin
9.1 Introduction
9.2 Non-inferiority versus Similarity
9.2.1 Relationship among Non-inferiority, Equivalence, and Superiority
9.2.2 Impact on Sample Size Requirement
9.3 Non-inferiority Hypothesis
9.3.1 Regulatory Requirements
9.3.2 Hypothesis Setting and Clinically Meaningful Margin
9.3.3 Retention of Treatment Effect in the Absence of Placebo
9.4 Methods for Selection of Non-inferiority Margin
9.4.1 Classical Method
9.4.2 FDA’s Recommendations
9.4.3 Chow and Shao’s Method
9.4.4 Alternative Methods
9.4.5 An Example
9.4.5 Remarks
9.5 Strategy for Margin Selection
9.5.2 Criteria for Risk Assessment
9.5.3 Risk Assessment with Continuous Endpoints
9.5.4 Numerical Studies
9.5.5 An Example
9.6 Concluding Remarks
References
10. Design and Analysis of Biosimilar Switching Studies
10.1 Introduction
10.2 Interchangeable Biosimilar Product
10.3 Switching Designs
10.3.1 The 2 × (m + 1) Crossover Design
10.3.2 Complete n-of-1 Trial Design
10.4 Statistical Model and Analysis
10.4.1 Statistical Model
10.4.2 Analysis of FDA Recommended Switching Design with Three Switches
10.4.3 Analysis of Complete n-of-1 Design with Three Switches
10.4.4 A Comparison
10.5 Sample Size Requirement
10.6 Concluding Remarks
References
Appendix
Hypothesis Based on Additive Effect
Hypothesis Based on Multiplicative Effect
11. Detecting Reference Product Change in Biosimilar Studies
11.1 Introduction
11.2 Statistical Test
11.2.1 Notation and Data
11.2.2 Detection of Change Points
11.2.3 Hypotheses Testing for Mean/Variability Drifts
11.3 Simulation Study
11.4 An Example
11.5 Concluding Remarks
References
12. Sensitivity Analysis for Assessment of Extrapolation
12.1 Introduction
12.2 Shift in Target Patient Population
12.3 Assessment of Sensitivity Index
12.3.1 The Case Where e Is Random and C Is Fixed
12.3.2 The Case Where e Is Fixed and C Is Random
12.3.3 The Case Where Both e and C are Random
12.4 Statistical Inference
12.4.1 The Case Where e Is Random and C Is Fixed
12.4.2 The Case Where e Is Fixed and C Is Random
12.4.3 The Case Where Both e and C Are Random
12.4.4 Confidence Interval of the Effect Size in Original Population
12.5 An Example
12.6 Concluding Remarks
References
Appendix
13. Non-Medical Switch
13.1 Introduction
13.2 Approaches for Evaluation of Non-Medical Switch
13.2.1 Single Arm Observational Studies
13.2.2 Clinical Studies
13.3 Scientific Factors and Statistical Considerations
13.3.1 Scientific Factors
13.3.2 Statistical Considerations
13.4 Design and Analysis of Switching Studies
13.4.1 Study Designs
13.5 Concluding Remarks
References
14. Case Studies
14.1 Case Study I: Remsima®
14.1.1 Overview of Remsima®
14.1.2 Analytical Similarity
14.1.2.1 Analytical Similarity Assessment
14.1.2.2 Analytical Similarity Conclusions
14.1.3 Clinical Program
14.1.3.1 Clinical Pharmacokinetics
14.1.3.2 Clinical Efficacy
14.1.3.3 Clinical Safety
14.1.3.4 Conclusion
14.2 Case Study II: MVASI®
14.2.1 Overview of MVASI®
14.2.2 Analytical Similarity
14.2.2.1 Analytical Similarity Assessment
14.2.2.2 Analytical Similarity Conclusions
14.2.3 Clinical Similarity
14.2.3.1 Clinical Pharmacokinetics
14.2.3.2 Clinical Efficacy
14.2.3.3 Clinical Safety
14.2.3.4 Immunogenicity
14.2.3.5 Conclusion
14.3 Case Study III: TRUXIMA®
14.3.1 Overview of TRUXIMA®
14.3.2 Analytical Similarity
14.3.2.1 Analytical Similarity Assessment
14.3.2.2 Analytical Similarity Conclusions
14.3.3 Clinical Similarity
14.3.3.1 Clinical Pharmacokinetics
14.3.3.2 Clinical Efficacy
14.3.3.3 Clinical Safety
14.3.3.4 Immunogenicity
14.3.3.5 Conclusion
14.4 Case Study IV: AMJEVITA®
14.4.1 Overview of AMJEVITA®
14.4.2 Analytical Similarity
14.4.2.1 Analytical Similarity Assessment
14.4.2.2 Analytical Similarity Conclusions
14.4.3 Clinical Similarity
14.4.3.1 Clinical Pharmacokinetics
14.4.3.2 Clinical Efficacy
14.4.3.3 Clinical Safety
14.4.3.4 Immunogenicity
14.4.3.5 Conclusion
References
14.5.1 References for 14.1 Remsima®
14.5.2 References for 14.2 Mvasi®
14.5.3 References for 14.3 Truxima®
Index