Bayesian Design of Proof-of-Concept Trials.

The proof-of-concept (PoC) decision is a key milestone in the clinical development of an experimental treatment. A decision is taken on whether the experimental treatment is further developed (GO), whether its development is stopped (NO-GO), or whether further information is needed to make a decision. The PoC decision is typically based on a PoC clinical trial in patients comparing the experimental treatment with a control treatment. It is important that the PoC trial be designed such that a GO/NO-GO decision can be made. The present work develops a generic, Bayesian framework for defining quantitative PoC criteria, against which the PoC trial results can be assessed. It is argued that PoC criteria based solely on significance testing versus the control are not appropriate in this decision context. A dual PoC criterion is proposed that includes assessment of superiority over the control and relevance of the effect size and hence better matches clinical decision making. The approach is illustrated for 2 PoC trials in cystic fibrosis and psoriasis.