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• W2014509194 abstract "Bioequivalence or interaction trials are commonly studied in crossover design and can be analysed by nonlinear mixed effects models as an alternative to noncompartmental approach. We propose an extension of the population Fisher information matrix in nonlinear mixed effects models to design crossover pharmacokinetic trials, using a linearisation of the model around the random effect expectation, including within‐subject variability and discrete covariates fixed or changing between periods. We use the expected standard errors of treatment effect to compute the power for the Wald test of comparison or equivalence and the number of subjects needed for a given power. We perform various simulations mimicking crossover two‐period trials to show the relevance of these developments. We then apply these developments to design a crossover pharmacokinetic study of amoxicillin in piglets and implement them in the new version 3.2 of the r function PFIM. Copyright © 2011 John Wiley & Sons, Ltd." @default.
• W2014509194 created "2016-06-24" @default.
• W2014509194 creator A5052803368 @default.
• W2014509194 creator A5079124343 @default.
• W2014509194 date "2011-10-03" @default.
• W2014509194 modified "2023-10-07" @default.
• W2014509194 title "Design evaluation and optimisation in crossover pharmacokinetic studies analysed by nonlinear mixed effects models" @default.
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• W2014509194 doi "https://doi.org/10.1002/sim.4390" @default.
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