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Updated: Feb 13, 2026

Assembly, Loading, and Alignment of an Analytical Ultracentrifuge Sample Cell
Published on: November 5, 2009
On sample size requirement for analytical similarity assessment
Yi Zhao1, Yu-Wei Chang2, Shein-Chung Chow1
1a Department of Biostatistics and Bioinformatics , Duke University School of Medicine , Durham , North Carolina , USA.
This study discusses the U.S. Food and Drug Administration's (FDA) proposal for selecting sample sizes in biosimilar analytical similarity testing. It analyzes how adjusting equivalence acceptance criteria (EAC) and variability impacts sample size requirements for biosimilar product approval.
Area of Science:
- Biopharmaceutical Sciences
- Regulatory Science
- Statistical Analysis
Background:
- The U.S. Food and Drug Administration (FDA) utilizes a stepwise approach to evaluate biosimilarity between proposed biosimilar and reference biologic products.
- Analytical similarity assessment of critical quality attributes (CQAs) is the initial step, focusing on structural, physicochemical, and functional properties.
- For Tier 1 CQAs, equivalence testing with an equivalence acceptance criterion (EAC) is recommended for similarity assessment.
Purpose of the Study:
- To discuss the FDA's proposal for selecting appropriate sample sizes in biosimilar equivalence testing.
- To analyze the impact of adjusting the equivalence acceptance criterion (EAC) margin and variability on sample size requirements.
- To conduct a numerical study comparing sample size needs under various parameter combinations.
Main Methods:
- Discussion of the FDA's proposed methodology for sample size determination in biosimilar analytical similarity testing.
- Description of sample size requirements under different scenarios, considering EAC margin and variability.
- Conducting a numerical study to compare sample size requirements across various combinations of study parameters.
Main Results:
- The study provides a thorough discussion on the FDA's proposal for sample size selection.
- Sample size requirements are described under different scenarios.
- A numerical study compares sample size requirements under various combinations of study parameters, highlighting the interplay between EAC, variability, and sample size.
Conclusions:
- Appropriate sample size selection is critical for robust biosimilar equivalence testing.
- Adjusting the equivalence acceptance criterion (EAC) margin and variability significantly influences sample size requirements.
- The findings support informed decision-making in the design of analytical similarity studies for biosimilar product development and regulatory approval.
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