Design of population pharmacokinetic experiments using prior information

Abstract

A population pharmacokinetic study design is a group of elementary designs each composed of a set of sampling times to be performed in a number of subjects in the design. Design factors such as the number of elementary designs, proportion of subjects in each elementary design, number of samples per subject, and sampling times in the subjects need to be carefully balanced in the design of a study. An optimally designed population pharmacokinetic study will give the best combination of these design factors and involves application of statistical experimental design principles to non-linear population pharmacokinetic models. Information from previous experiments, the literature, and experience in the form of model and parameter estimates are used to design a future study by optimization of a design criterion within some constraints. This work provides a brief background of approaches to the designs of a population pharmacokinetic experiment and a review of optimal design methodologies that have been developed for designing population pharmacokinetic experiments. Computer application programs and software that have been developed together with options available in them are also reviewed.

• Population pharmacokinetics
• optimal design
• D-optimality
• simulation
• mixed-effects
• Fisher information matrix