Optimal Designs for Dose-Finding Studies

Abstract

Understanding and properly characterizing the dose–response relationship is a fundamental step in the investigation of a new compound, be it a herbicide or fertilizer, a molecular entity, an environmental toxin, or an industrial chemical. In this article we investigate the problem of deriving efficient designs for the estimation of target doses in the context of clinical dose finding. We propose methods to determine the appropriate number and actual levels of the doses to be administered to patients, as well as their relative sample size allocations. More specifically, we derive local optimal designs that minimize the asymptotic variance of the minimum effective dose estimate under a particular dose–response model. We investigate the small-sample properties of these designs, together with their sensitivity to a misspecification of the true parameter values and of the underlying dose–response model, through simulation. Finally, we demonstrate that the designs derived for a fixed model are rather sensitive with respect to this assumption and construct robust optimal designs that take into account a set of potential dose–response profiles within classes of models commonly used in drug development practice.