Construction of an optimal destructive sampling design for noncompartmental AUC estimation

Abstract

Based on toxicokinetic studies of a destructive sampling design, this work was aimed at selecting the number of time points, their locations, and the number of replicates per time point in order to obtain the most accurate and precise noncompartmental estimate of the area under the concentration-time curve (AUC). From a prior population pharmacokinetic model, the design is selected to minimize the scaled mean squared error of AUC. Designs are found for various sample sizes, number of time paints, and a distribution of animals across time points from being very unbalanced to balanced. Their efficiencies are compared both theoretically and based on simulations. An algorithm has been implemented for this purpose using the symbolic resolution and numerical minimization capabilities of Mathematica(TM) and an example of its use is provided. This method provides efficient tools for constructing, validating and comparing optimal sampling designs for destructive sampled toxicokinetic studies.