TY - JOUR T1 - On Statistical Approaches for Demonstrating Analytical Similarity in the Presence of Correlation JF - PDA Journal of Pharmaceutical Science and Technology JO - PDA J Pharm Sci Technol SP - 547 LP - 559 DO - 10.5731/pdajpst.2016.006551 VL - 70 IS - 6 AU - Harry Yang AU - Steven Novick AU - Richard K. Burdick Y1 - 2016/11/01 UR - http://journal.pda.org/content/70/6/547.abstract N2 - 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. ER -