Efficient algorithms for calculating optimal designs in pharmacokinetics and dose finding studies

Abstract

Random effects models are widely used in population pharmacokinetics and dose finding studies. In such models the presence of correlated observations (due to shared random effects and possibly residual serial correlation) usually makes the explicit determination of optimal designs diffcult. In this paper we develop a class of multiplicative algorithms for the numerical calculation of optimal experimental designs in such situations. In particular we demonstrate its application in a concrete example of a cross-over dose finding trial. Additionally, we show that the methodology can be modified to determine optimal designs where there exist some requirements regarding the minimal number of treatments for several (in some cases all) experimental conditions. AMS Subject Classi cation: 62K05