NDLI: Likelihood approach for evaluating bioequivalence of highly variable drugs.

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Likelihood approach for evaluating bioequivalence of highly variable drugs.

Content Provider	World Health Organization (WHO)-Global Index Medicus
Author	Du, Liping Choi, Leena
Spatial Coverage	United States
Description	Country affiliation: United States Author Affiliation: Du L ( Vanderbilt Center for Quantitative Sciences, Vanderbilt University, Nashville, TN, USA.)
Abstract	Bioequivalence (BE) is required for approving a generic drug. The two one-sided tests procedure (TOST, or the 90% confidence interval approach) has been used as the mainstream methodology to test average BE (ABE) on pharmacokinetic parameters such as the area under the blood concentration-time curve and the peak concentration. However, for highly variable drugs (%CV > 30%), it is difficult to demonstrate ABE in a standard cross-over study with the typical number of subjects using the TOST because of lack of power. Recently, the US Food and Drug Administration and the European Medicines Agency recommended similar but not identical reference-scaled average BE (RSABE) approaches to address this issue. Although the power is improved, the new approaches may not guarantee a high level of confidence for the true difference between two drugs at the ABE boundaries. It is also difficult for these approaches to address the issues of population BE (PBE) and individual BE (IBE). We advocate the use of a likelihood approach for representing and interpreting BE data as evidence. Using example data from a full replicate 2 × 4 cross-over study, we demonstrate how to present evidence using the profile likelihoods for the mean difference and standard deviation ratios of the two drugs for the pharmacokinetic parameters. With this approach, we present evidence for PBE and IBE as well as ABE within a unified framework. Our simulations show that the operating characteristics of the proposed likelihood approach are comparable with the RSABE approaches when the same criteria are applied.
File Format	HTM / HTML
ISSN	15391604
e-ISSN	15391612
DOI	10.1002/pst.1661
Journal	Pharmaceutical Statistics
Issue Number	2
Volume Number	14
Language	English
Publisher	Wiley
Publisher Date	2015-03-01
Publisher Place	Great Britain (UK)
Access Restriction	Open
Subject Keyword	Discipline Statistics Discipline Pharmacology Drug Evaluation, Preclinical Drugs, Generic Pharmacokinetics Pharmaceutical Preparations Metabolism United States Food And Drug Administration Cross-over Studies Administration & Dosage Likelihood Functions Therapeutic Equivalency Research Support, N.i.h., Extramural
Content Type	Text
Resource Type	Article
Subject	Statistics and Probability Pharmacology Pharmacology (medical)

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