AI-Driven Recruitment for Alzheimer’s Disease Clinical Trials: A Pilot Analysis on the A4 Study Dataset
Efficient recruitment in Alzheimer’s disease (AD) trials is challenging, and early use of sensitive biomarkers can reduce screen failures and costs. We evaluated an MRI-based machine learning model, previously trained to classify AD, FTD, normal controls, and other dementias, as a pre-screening tool using A4 Study data.
Neuroimaging Biomarkers for Friedreich Ataxia: A Cross-Sectional Analysis of the TRACK-FA Study
Neuroimaging Biomarkers for Friedreich Ataxia: A Cross-Sectional Analysis of the TRACK-FA Study Objective Our study aims to quantify differences in the brain and spinal cord between individuals with Friedreich's ataxia and healthy controls. This includes stratification by age and disease stage, and for the first time, the inclusion of young children.
Comparison of two natural history studies as part of the HD-IH consortium: a use case for historical external control group matching in clinical trials
External control groups can support regulatory decision-making in clinical trials, especially rare diseases. In Huntington’s disease (HD) there is a wealth of historical data, but matching historical data to clinical trials is challenging.