A Quantitative Approach for Making Go/No-Go Decisions in Drug Development

There are many decision points along the product development continuum. Formal clinical milestones, such as the end of phase 1, phase 2a (proof of mechanism or proof of concept), and phase 2b provide useful decision points to critically evaluate the accumulating data. At each milestone, sound decisions begin with asking the right questions and choosing the appropriate design as well as criteria to make go/no-go decisions. It is also important that knowledge about the new investigational product, gained either directly from completed trials or indirectly from similar products for the same disorder, be systematically incorporated into the evaluation process. In this article, we look at metrics that go beyond type I and type II error rates associated with the traditional hypothesis test approach. We draw on the analogy between diagnostic tests and hypothesis tests to highlight the need for confirmation and the value of formally updating our prior belief about a compound’s effect with new data. Furthermore, we show how incorporating probability distributions that characterize current evidence about the true treatment effect could help us make decisions that specifically address the need at each clinical milestone. We illustrate the above with examples.