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. Read the abstract, originally  presented at AAIC 2022, to learn more about how 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.