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Subject-by-Formulation Interaction in Determinations of Individual Bioequivalence: Bias and Prevalence
Authors:Endrenyi  Laszlo  Tothfalusi  Laszlo
Institution:(1) Department of Pharmacology, University of Toronto, Toronto, Ontario, M5S 1A8, Canada;(2) Department of Pharmacodynamics, Semmelweis Medical University, Budapest, Hungary
Abstract:Purpose. 1. To determine properties of the estimated variance component for the subject-by-formulation interaction (sgr2 D) in investigations of individual bioequivalence (IBE), and 2. to evaluate the prevalence of interactions in replicate-design studies published by FDA. Methods. Four-period crossover studies evaluating IBE were simulated repeatedly. Generally, the true bioequivalence of the two formulations, including sgr2 D= 0, was assumed, sgr2 D was then estimated in a linear mixed-effect model by restricted maximum likelihood (REML). The same method was applied for estimating sgr2 D for the data sets of FDA. Results. 1.sgrD estimated by REML was positively biased. The bias and dispersion of the estimated sgrDincreased approximately linearly with the estimated within-subject standard deviation for the reference formulation (sgrWR). Only a small proportion of the estimated sgrD exceeded the estimated sgrWR. 2. Distributions of the estimated sgrD were evaluated. At sgrWR = 0.30, a level of estimated sgrD= 0.15 was exceeded, by random chance, with a probability of about 25%. 3. Importantly, the behaviour of the sgr2 D values estimated from the FDA data sets was similar to that exhibited by the simulated estimates of sgr2 D which were generated under the conditions of true bioequivalence. Conclusions. 1. sgrD estimated by REML is biased; the bias increases proportionately with the estimated sgrWR. Consequently, exceeding a fixed level of sgrD (e.g., 0.15) does not indicate substantial interaction. 2. The data sets of FDA are compatible with the hypothesis of sgr2 D = 0. Consequently, they do not demonstrate the prevalence of subject-by-formulation interaction. Therefore, it could be sufficient and reasonable to evaluate bioequivalence from 2-period crossover studies.
Keywords:individual bioequivalence  regulatory criterion  intra-subject variation  subject-by-formulation interaction  crossover design  maximum likelihood
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