Keywords: Proof of Concept, Go/No Go Decisions, Proof of Mechanism, Predictive Probability
In all phases of drug development, late-phase failure is a recognized industry-wide problem that can be detrimental not only to the industry’s overall R&D objectives but also to the patient in the sense of not getting access to effective and safe treatments if in fact the clinical trials are continued to their completion. Proof of Concept (POC) trials are designed to demonstrate how a drug interacts correctly with its molecular target and, in turn, alter the disease. A POC trial plays a crucial role at the early stage and the road to achieving a POC must go through at least two critical trigger points, confirmation of Proof of Mechanism (POM) and Early Sign of Efficacy (ESoE). In most of these stages, especially studies involving ESoE and/or POC, there exists plethora of opportunities for a team to make quantitative decisions to move forward to the next stage. At late stages (late Phase-II or III) that typically include large number of patients, primary endpoint analyses have included group sequential methods, which allow early stopping for e?cacy in light of compelling evidence of bene?t or early stopping for futility when the likelihood of success is low at interim analyses, for many years. But, early stages studies such as ESoE or POC that only involve small number of patients may have to rely on the use of unconventional thinking including Bayesian methods and other approaches for decision making. Posterior probabilities are extremely useful and informative for making three critical decisions based on pre-defined target value: stop for futility (No Go), progress with caution (gray zone, Go Slow), accelerate development (Go Fast). Bayesian approaches with the use of a target value and associated posterior probability, provide direct answers to making these decisions. In this presentation, we will provide detailed discussions on the early drug development paradigm where Bayesian approaches can be judiciously used for critical decision making.