Abstract
The Bayesian approach to inference and decision making provides an integrated way of addressing the various aspects of drug development, from the early preclinical study of compounds through the clinical and postmarketing phases. In particular, it provides a natural, convenient way for choosing among experimental designs. An essential aspect of the process of evaluating design strategies is the ability to calculate predictive probabilities of potential results. I describe a Bayesian approach to experimental design and illustrate it by considering a particular type of clinical trial. Also, I compare Bayesian and classical statistical attitudes toward design.

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