Efficient model-based bioequivalence testing
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Date
2019
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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.
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Keywords
bioequivalence, two one-sided tests, noncompartmental bioequivalence analysis, pharmacokinetics, nonlinear mixed effects model