POWER-TRANSFORMATION MIXED EFFECTS MODEL WITH APPLICATIONS TO PHARMACOKINETICS(Statistical Models for Biomedical Research)

Pharmacokinetics is the study of the time course of disposition of a drug in the human body of an individual or a group of individuals on the basis of blood drug concentration data for each individual. In this paper, intending to characterize the pharmacokinetics of the group of individuals in aggregate, we proposed the powertransformation mixed effects model, and evaluated its performance by an example from the pharmacokinetic literature and a simulation experiment. In the investigation of the literature example, we compared the performance of the power-transformation mixed effects model with that of the no-transformation mixed effects model. As a consequence, the power-transformation mixed effects model could deal with the heteroscedasticity of the observed drug concentration appropriately. In the simulation experiment, we evaluated the performance of the estimations of the fixed effects parameters and the elements in the variance-covariance matrix of the random effects in the power-transformation mixed effects model and the no-transformation mixed effects model, in the setting of a situation where the blood drug concentration data have heteroscedasticity. We evaluated the effects of the number of individuals, the type of selection of the sampling times of the blood drug concentrations, and the variability of the error distribution on the estimations of the parameters in both models. As a result, the power-transformation mixed effects model was very useful as an approach to pharmacokinetics.