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Research ArticleResearch

On Statistical Approaches for Demonstrating Analytical Similarity in the Presence of Correlation

Harry Yang, Steven Novick and Richard K. Burdick
PDA Journal of Pharmaceutical Science and Technology November 2016, 70 (6) 547-559; DOI: https://doi.org/10.5731/pdajpst.2016.006551
Harry Yang
1MedImmune, LLC; and
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  • For correspondence: YangH@MedImmune.com
Steven Novick
1MedImmune, LLC; and
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Richard K. Burdick
2Elion Labs
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Abstract

Analytical similarity is the foundation for demonstration of biosimilarity between a proposed product and a reference product. For this assessment, currently the U.S. Food and Drug Administration (FDA) recommends a tiered system in which quality attributes are categorized into three tiers commensurate with their risk and approaches of varying statistical rigor are subsequently used for the three-tier quality attributes. Key to the analyses of Tiers 1 and 2 quality attributes is the establishment of equivalence acceptance criterion and quality range. For particular licensure applications, the FDA has provided advice on statistical methods for demonstration of analytical similarity. For example, for Tier 1 assessment, an equivalence test can be used based on an equivalence margin of 1.5 σR, where σR is the reference product variability estimated by the sample standard deviation SR from a sample of reference lots. The quality range for demonstrating Tier 2 analytical similarity is of the form X̄R ± K × σR where the constant K is appropriately justified. To demonstrate Tier 2 analytical similarity, a large percentage (e.g., 90%) of test product must fall in the quality range. In this paper, through both theoretical derivations and simulations, we show that when the reference drug product lots are correlated, the sample standard deviation SR underestimates the true reference product variability σR. As a result, substituting SR for σR in the Tier 1 equivalence acceptance criterion and the Tier 2 quality range inappropriately reduces the statistical power and the ability to declare analytical similarity. Also explored is the impact of correlation among drug product lots on Type I error rate and power. Three methods based on generalized pivotal quantities are introduced, and their performance is compared against a two-one-sided tests (TOST) approach. Finally, strategies to mitigate risk of correlation among the reference products lots are discussed.

LAY ABSTRACT: A biosimilar is a generic version of the original biological drug product. A key component of a biosimilar development is the demonstration of analytical similarity between the biosimilar and the reference product. Such demonstration relies on application of statistical methods to establish a similarity margin and appropriate test for equivalence between the two products. This paper discusses statistical issues with demonstration of analytical similarity and provides alternate approaches to potentially mitigate these problems.

  • Acceptance criteria
  • Analytical similarity
  • Biosimilar
  • Equivalence testing
  • Generalized pivotal quantity
  • Stepwise approach
  • © PDA, Inc. 2016
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PDA Journal of Pharmaceutical Science and Technology: 70 (6)
PDA Journal of Pharmaceutical Science and Technology
Vol. 70, Issue 6
November/December 2016
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On Statistical Approaches for Demonstrating Analytical Similarity in the Presence of Correlation
Harry Yang, Steven Novick, Richard K. Burdick
PDA Journal of Pharmaceutical Science and Technology Nov 2016, 70 (6) 547-559; DOI: 10.5731/pdajpst.2016.006551

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On Statistical Approaches for Demonstrating Analytical Similarity in the Presence of Correlation
Harry Yang, Steven Novick, Richard K. Burdick
PDA Journal of Pharmaceutical Science and Technology Nov 2016, 70 (6) 547-559; DOI: 10.5731/pdajpst.2016.006551
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    • Abstract
    • 1. Introduction
    • 2. Analytical Similarity Assessment
    • 3. Comparison of Statistical Approaches with Correlation among Lots
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Keywords

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  • generalized pivotal quantity
  • Stepwise approach

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