Live sessions will be held 8:30-noon, PT (11:30-3 p.m. ET) each day. Pre-recorded lectures, downloadable presentations, data sets and other course materials will be posted prior to the start of the module.

The course will introduce Bayesian adaptive designs and cover numerous examples ranging from early to late stage trials. It will describe the range of potential adaptations and include operational benefits and challenges.

The course will introduce students to the skills and considerations necessary to construct such designs, including how to select design parameters based upon simulating trial operating characteristics. We will learn to compare designs to one another and fixed on numerous performance metrics.

The course will illustrate Platform trials involving multiple drugs, Goldilocks trials for pivotal trials using predictive probabilities for sample size selection, and dose-finding studies. We will also discuss operational aspects and challenges that arise when conducting an adaptive trial.

Some knowledge of clinical trials and statistics is necessary, though a Bayesian background is not.