Abstract
The design of pharmacokinetic and pharmacodynamic experiments concerns a number of issues, among which are the number of observations and the times when they are taken. Often a model is used to describe these data and the pharmacokinetic–pharmacodynamic behavior of a drug. Knowledge of the data analysis model at the design stage is beneficial for collecting patient data for parameter estimation. A number of criteria for model-oriented experiments, which maximize the information content of the data, are available. In this paper we present a program, Popdes, to investigate the D-optimal design of individual and population multivariate response models, such as pharmacokinetic–pharmacodynamic, physiologically based pharmacokinetic, and parent drug and metabolites models. A pre-clinical and clinical pharmacokinetic–pharmacodynamic model describing the concentration–time profile and effect of an oncology compound in development is used for illustration.
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