We describe the development of a Bayesian adaptive platform trial for determining the effectiveness of therapies for Alzheimer's Disease (AD). AD is the leading cause of dementia globally. Current approved therapies have only been shown to slow the worsening of symptoms but not alter the disease progression.
Our primary interest is in developing a platform trial with the infrastructure that enables simultaneous evaluation of multiple potential disease modifying therapies in individuals at risk for AD. The trial follows a two-stage design. The goal of the first stage is the demonstration of target biomarker modulation. The goal of the second stage is the demonstration of efficacy in terms of a cognitive benefit. Several innovative aspects of the design include: pooling of information from placebo patients across regimens, proposing to stop a regimen early for lack of biomarker efficacy, and proposing to advance the regimen to the cognitive endpoint stage due to positive benefit on the targeted biomarker.
Within our presentation we highlight the importance of clinical trial simulation in specifying key design parameters.
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