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A Further Look at the Current Equivalence Test for Analytical Similarity Assessment

  • Neal Thomas
  • Aili ChengEmail author
Conference paper
Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 218)

Abstract

Establishing analytical similarity is the foundation of biosimilar product development. Although there is no guidance on how to evaluate analytical data for similarity, the US Food and Drug Administration (FDA) recently suggested an equivalence test on the mean difference between innovator and the biosimilar product as the statistical similarity assessment for Tier 1 quality attributes (QAs), defined as the QAs that are directly related to the mechanism of action. However, the mathematical derivation and simulation work presented in this paper shows that the type I error is typically increased in most realistic settings when an estimate of sigma is used for the equivalence margin. This error cannot be improved by increasing sample size. The impacts of the constant c on type I error and sample size adjustment in the imbalanced situation are discussed, as well.

Keywords

Equivalence testing Type I error rate Sample size adjustment 

Notes

Acknowledgements

The authors thank Ira Jacobs for providing the background information for Fig. 1.

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Copyright information

© Pfizer, Inc. 2019

Authors and Affiliations

  1. 1.Pfizer, Statistical Research and Consulting CenterGrotonUSA
  2. 2.Pfizer, Pharmaceutical Sciences and Manufacturing StatisticsAndoverUSA

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