Incorporating Correlation in Interindividual Variability for the Optimal Design of Multiresponse Pharmacokinetic Experiments

This paper presents a method for optimal design of multiresponse population pharmacokinetic experiments taking into account correlations between interindividual variances. Expressions for the population Fisher information matrix have been defined for uniresponse and multiresponse pharmacokinetic experiments. A major assumption often made is that the variance–covariance matrix of the interindividual variance components has only diagonal elements so that whenever intersubject covariance elements are present, they are ignored during the design of the experiment. Recently expressions that accounted for these off diagonal elements were developed for uniresponse population pharmacokinetic experiments. The work presented here extends these expressions to multiresponse population pharmacokinetic experiments. These were applied to a population pharmacokinetic model, a population pharmacokinetic–pharmacodynamic model, and a parent–metabolite pharmacokinetic model example. The results obtained showed that optimal de...