Sample size reduction in preclinical experiments: A Bayesian sequential decision-making framework.

Abstract

When animals are used in a preclinical experiment, ethical concerns may arise regarding animal welfare. The 3Rs principles were developed to guide more humane animal research practices. This article specifically addresses the reduction aspect of the 3Rs. Under our proposed framework, the preclinical experiment is conducted sequentially, and at every stage of the experiment we examine the outcome and decide whether to stop early for efficacy or futility. Compared to traditional methods in the literature, which typically only check for efficacy, the proposed method has the potential to further reduce the number of animals needed in an experiment. The proposed design requires specifying loss functions at every stage of the experiment. These functions may be directly related to the actual cost of conducting the study or can be calibrated to reflect the prior belief that the drug will be effective. Decisions are made based on minimizing the posterior expected loss. We evaluate the design methodology through simulation studies that involve two-arm experiments with either binary or continuous endpoints. Additionally, we also provide examples taken from real preclinical experiments.