A digital twin technique using external observational data to reduce sample sizes in clinical trials on Alzheimer’s disease
Abstract
Randomized placebo‐controlled trials (RCTs) are the gold standard to evaluate efficacy of new drug treatments for Alzheimer’s disease. For example, the United States FDA approved the brain amyloid‐targeting drug lecanemab following CLARITY AD, Biogen and Eisai’s Phase 3 RCT. However, recruiting enough participants for a high‐powered and demographically representative trial is difficult and expensive. Fortunately, historical patient data from existing external observational studies of a disease can help populate RCTs [Thorlund et al. (2020). https://doi.org/10.2147/CLEP.S242097]. We propose a new trial framework that uses an external study to source “digital twins” for each trial participant. Using computer‐simulated trials mimicking CLARITY AD’s demographics and 18‐month duration, we show that our digital twin trial (DTT) has increased power compared to a conventional RCT.
How strong is the evidence?
Evidence Hub reads this as a randomized trial, done in people. Its evidence level is 2 of 5 (High · randomized trial). Randomized trials of a reasonable size are the strongest single-study design.
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