Analytical Similarity Assessment in Biosimilar Product Development

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.

Introduction Background Past Experience for In Vitro Bioequivalence Testing Analytical Similarity Assessment Scientific Factors and practical issues Aim and Scope of the Book Regulatory Approval Pathway of Biosimilar Products Introduction Regulatory requirements Analytical Studies for Functional/Structural Characterization Global harmonization Concluding remarks CMC Requirements Introduction CMC Development Manufacturing Process Validation Quality Control and Assurance Stability Analysis Concluding Remarks Assay Development and Process Validation Introduction Regulatory Requirements Analytical Method Validation Analysis of Validation Data Evaluation of Reliability, Repeatability, and Reproducibility Concluding remarks Critical Quality Attributes Introduction Identification of CQAs Classification of CQAs Concluding Remarks FDA Tiered Approach for Analytical Assessment Background Stepwise Approach Tier Equivalence Test Other tiered approaches Some Practical Considerations Concluding Remarks Sample Size Requirement Introduction Traditional Approach FDA’s Current Thinking and Recommendation Sample Size Requirement Numerical Studies Concluding remarks Multiple References Background Method of Pairwise Comparisons Simultaneous Confidence Interval Reference Product Change Concluding remarks Extrapolation Across Indications Introduction An Example Development of Sensitivity Index Assessment of Sensitivity Index Statistical Inference of Extrapolation Concluding Remarks Case Studies - FDA Submissions FDA Abbreviated Licensure Pathway Sponsor’s Strategy for Regulatory Submission Avastin Biosimilar Regulatory Submission Herceptin Biosimilar Regulatory Submission Concluding Remarks Practical and Challenging Issues Introduction Hypotheses versus Confidence Interval Approach Totality-of-the-evidence Inconsistencies Between Tired Approaches Individual bioequivalence Commonly Asked Questions from the Sponsors Concluding Remarks Recent Development Introduction Comparing Means versus Comparing Variances Switching Design Non-Medical Switching FDA guidance on Analytical Similarity Assessment Concluding Remarks

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.