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.