Checking distributional assumptions for pharmacokinetic summary statistics based on simulations with compartmental models.
Bioequivalence (BE) studies are an essential part of the evaluation of generic drugs. The most common in vivo BE study design is the two-period two-treatment crossover design. AUC (area under the concentration-time curve) and Cmax (maximum concentration) are obtained from the observed concentration-time profiles for each subject from each treatment under each sequence. In the BE evaluation of pharmacokinetic crossover studies, the normality of the univariate response variable, e.g. log(AUC)1or log(Cmax), is often assumed in the literature without much evidence. Therefore, we investigate the distributional assumption of the normality of response variables, log(AUC) and log(Cmax), by simulating concentration-time profiles from two-stage pharmacokinetic models (commonly used in pharmacokinetic research) for a wide range of pharmacokinetic parameters and measurement error structures. Our simulations show that, under reasonable distributional assumptions on the pharmacokinetic parameters, log(AUC) has heavy tails and log(Cmax) is skewed. Sensitivity analyses are conducted to investigate how the distribution of the standardized log(AUC) (or the standardized log(Cmax)) for a large number of simulated subjects deviates from normality if distributions of errors in the pharmacokinetic model for plasma concentrations deviate from normality and if the plasma concentration can be described by different compartmental models.
a Center for Drug Evaluation and Research , U.S. Food and Drug Administration , Silver Spring , Maryland , USA.
Meiyu
M
Shen
b Center for Biologics Evaluation and Research , U.S. Food and Drug Administration , Silver Spring , Maryland , USA.
Estelle
E
Russek-Cohen
c Mathematics Department , University of Maryland , College Park , Maryland , USA.|d Center for Statistical Research and Methodology , U.S. Census Bureau , Maryland , USA.
Eric V
EV
Slud
D019540:Area Under Curve; D003198:Computer Simulation / Q000706:statistics & numerical data*; D016568:Drugs, Generic / Q000493:pharmacokinetics*; D006801:Humans; D010599:Pharmacokinetics; D016008:Statistical Distributions; D013810:Therapeutic Equivalency
D016568:Drugs, Generic
Bioequivalence; distributional assumption; normality; pharmacokinetic modeling