Applications of Digital Twins in Clinical Trials for Alzheimer’s Disease

AI-driven clinical trials have the potential to achieve higher power with fewer subjects, to provide actionable insights into which patients achieve the greatest benefit, and to design faster, more efficient clinical trials - all while ensuring reliable evidence about safety and efficacy. Digital Twins, or simulated control outcomes for individual patients, can be used to design trials that are smaller, faster, and/or more powerful. In this whitepaper, we describe 4 novel trial designs that balance three different characteristics: (i) the number of subjects required to achieve the power to detect a pre-specified effect size, (ii) insensitivity to potential confounding factors, and (iii) the type-I error rate, to demonstrate how Digital Twins can accelerate both early and late-stage clinical trials.

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Incorporating External Control Arms into Clinical Trials


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Synthetic Controls and Digital Twins both increase power, but only Digital Twins are robust to known as well as unknown confounders.