Authors: Möllenhoff, Kathrin
Loingeville, Florence
Bertrand, Julie
Nguyen, Thu Thuy
Sharan, Satish
Sun, Guoying
Grosser, Stella
Zhao, Liang
Fang, Lanyan
Mentré, France
Dette, Holger
Title: Efficient model-based bioequivalence testing
Language (ISO): en
Abstract: The classical approach to analyze pharmacokinetic (PK) data in bioequivalence studies aiming to compare two different formulations is to perform noncompartmental analysis (NCA) followed by two one-sided tests (TOST). In this regard the PK parameters AUC and Cmax are obtained for both treatment groups and their geometric mean ratios are considered. According to current guidelines by the U.S. Food and Drug Administration and the European Medicines Agency the formulations are deemed to be similar if the 90%- confidence interval for these ratios falls between 0:8 and 1:25. As NCA is not a reliable approach in case of sparse designs, a model-based alternative has already been proposed for the estimation of AUC and Cmax using non-linear mixed effects models. Here we propose another test than the TOST, called BOT, and evaluate it through a simulation study both for NCA and model-based approaches. For products with high variability on PK parameters, this method appears to have closer type I errors to the conventionally accepted significance level of 0:05, suggesting its potential use in situations where conventional bioequivalence analysis is not applicable.
Subject Headings: bioequivalence
two one-sided tests
noncompartmental bioequivalence analysis
nonlinear mixed effects model
Issue Date: 2019
Appears in Collections:Sonderforschungsbereich (SFB) 823

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