Abstract:
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Platform trials are an effective way for pharmaceutical companies to test divers treatments for a particular indication. There is a master protocol that defines design elements that are common across all individual studies within the platform trial and intervention specific appendices that describe the particulars for each intervention/treatment being considered. The main source of efficiency is in the possible use of shared placebo information across studies within the platform trial. Using the motivating example of a platform trial of the treatment of moderate to severely active Crohn’s disease, this paper will present a process and associated methodology, via the Bayesian framework, for using placebo data/information from external trials, as well as placebo data from other trials within the platform trial, to inform the design and inference of a given trial within the platform trial. Incorporating placebo information through prior probability distributions allow for more efficient designs, sharper inferential comparisons between treatment and placebo, and properly accounts for the uncertainty associated with the placebo parameter of interest.
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