In late-stage oncology drug development, drug developers have to make two critical Go-No Go decisions. The first one is whether to proceed to the definitive Phase III investigation after a Phase II proof-of-concept (POC) trial. The second one is whether to stop a Phase III confirmatory trial for futility after an interim analysis of the data. In practice, the two decisions are heuristically made with limited statistical input, usually amounting to statistical characterization of proposed options. We propose to find the optimal decisions by explicitly maximizing a benefit-cost ratio function, which is often the implicit objective in an otherwise qualitative decision-making process. The numerator of the function represents the benefit (proportional to the expected number of truly active drugs identified for Phase III development in the POC setting; proportional to the expected power for successful completion of Phase III in the interim analysis setting), and the denominator represents the expected total late-stage development cost. The method is easy to explain and simple to implement. The optimal design parameters provide a rational starting point for decision makers to consider. The method developed herein is directly applicable to portfolio management in the oncology therapeutic area where cost-effectiveness of a Go-No Go decision is a major concern. It is also applicable to other disease areas with the same concern or to similar decision issues at any stage of drug development.
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Chen et al. (2009) studied this question.
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