Optimal Sample Sizes and Go/No-Go Decisions for Phase II/III Development Programs Based on Probability of Success

Abstract

In the course of late-stage drug development, a phase II/III clinical development program faces a series of sample size planning and decision problems: the simultaneous sample sizes determination (SSD) across phase II and phase III trials at the program planning stage, the go/no-go decisions after phase II data have been observed, and the SSD of phase III trials incorporating phase II data. Conventionally, SSD are carried out on a trial-by-trial basis and independent of one another even though the trials are within the same program; and the go/no-go decisions are made based on the p-values, point estimates, and confidence intervals which may be, at times, ambiguous for decision making. In a combined empirical Bayesian and frequentist framework, this article proposes a probability of success (POS) function to allow an integrated approach to the SSD and go/no-go decision problems for a phase II/III program in which both the phase II and III trials share a common, normally distributed response variable. For the first time, optimal sample sizes can be determined simultaneously for a phase II/III program using the proposed POS function. As the POS function includes the conventional power function as a special case, it enjoys broader applications including SSD of phase II trials and that of phase III trials incorporating phase II data—neither of which can be handled as readily using the conventional power function.