We consider the use of external data (ED) in Bayesian adaptive platform designs. Ideally, the use of ED allows to largely reduce the number of patients allocated to the standard of care (SOC) arm,  retaining the same operative characteristics of standard Bayesian adaptive designs. However, if external data are not concordant with the internal trial data, inference can be severely biased, leading to inflations/deflations of the operating characteristics. We propose novel techniques for the inclusion of external data that provide robust estimations and satisfies a set of constraints on the study's operating characteristics required by regulators.

Leveraging external data in Bayesian adaptive platform designs

Regulatory Science Forum

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