Phase <scp>III</scp> Probability of Success When Early Development Is Based on a Putative Surrogate Endpoint: A Vaccine Efficacy Case Study

As Phase III trial costs and durations rise, pharmaceutical companies increasingly use quantitative methods to decide if a drug should progress beyond Phase II. A key method is the probability of success (PoS) for Phase III, calculated using the power function averaged across a treatment effect distribution estimated from Phase II. This paper explores PoS's role, particularly in moving from Phase II trials with putative surrogate endpoints to Phase III trials with clinical endpoints. Since the relationship between these endpoints is often unknown, expert input is necessary (prior elicitation). We propose the bivariate meta-analysis and a copula-based extension to characterize their relationship, using visual tools to simplify parameter elicitation. Specifically, we begin by eliciting the marginal distributions of the two quantities of interest. Then, to assist in eliciting the concordance parameter, we use the distribution of the treatment effect on the clinical endpoint conditional on the treatment effect on the putative surrogate. Our approach is illustrated in prophylactic vaccine development, linking immunological and clinical endpoints.