OPTIMUM DESIGN OF SAMPLING TIMES FOR INFERENCE OF COMPARTMENT MODELS BASED ON CURVATURE

Pharmacokinetics is the study of the time course of drug absorption, distribution, metabolization, and excretion in the human body. Actually, because we cannot monitor the kinetics of a drug in the human body directly, we observe the serial drug concentration in blood sampled from an individual who received the drug. In practice, intending to describe this time course in the observed drug concentration, we often use a compartment model. In this paper, we focus on nonlinearity of the compartment model and propose the design criterion, MSE_Q-D_<opt>, for the purpose of selecting the optimal sampling times of the blood drug concentration data. This criterion minimizes the determinant of the mean squared error for the estimates of the parameters in the compartment model. In several numerical examples, the properties of the MSE_Q-D_<opt> are evaluated. Furthermore, we assume a situation in which we fit the compartment model to the blood drug concentration data that are sampled at the times selected by the MSE_Q-D_<opt> and the typical optimal design criterion, D_<opt>, and evaluate the performance of their criteria for the estimation of the parameters in the compartment model. The MSE_Q-D_<opt> can select the sampling times flexibly and provide more precise estimates of the parameters, compared with the D_<opt>.