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