UCSF Rosenman Institute - The Health Technology Podcast #59: Digital Twins for Clinical Trials

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Publications

Modeling Disease Progression in Mild Cognitive Impairment and Alzheimer's Disease with Digital Twins

Publications

Bayesian prognostic covariate adjustment

Publications

Using Digital Twins to Decrease Enrollment and Increase Statistical Power in Alzheimer's Disease Trials (CTAD 2020)

We showed that digital twins could reduce the number of control subjects required in the analysis to achieve equivalent results to an analysis of the actual subjects.
Our novel method - Bayesian prognostic covariate adjustment - is a Bayesian analysis that draws on the strengths of the prognostic model approach.
Here, we have demonstrated that a particular type of generative model (i.e., CRBMs) can be used to accurately model disease progression for patients with MCI or AD.