Evaluating Digital Twins for Alzheimer’s Disease using Data from a Completed Phase 2 Clinical Trial

Complex Alzheimer’s Disease (AD) clinical trials that require a large number of subjects leads to long trial timelines and significant costs. Our novel methods can accelerate randomized clinical trials (RCT) by reducing the required number of subjects using a combination of deep learning‐based predictive models and statistical methods while meeting regulatory requirements. Our method leverages historical control clinical data in a way that allows for faster trials without sacrificing the reliability of traditional RCT analyses. A Phase 2 study on crenezumab (the ABBY study, NCT01343966) in mild‐to‐moderate AD was used to retrospectively assess the validity of this approach for AD clinical trials and the potential impact on future studies.