Irene Cumplido-Mayoral, PhD Candidate, Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain, comments on the most widely used applications of machine learning in Alzheimer’s disease (AD) research. One focus is using this technology to optimize clinical trial screening and recruitment. Researchers are developing models to determine which are the best combinations of biomarkers to detect amyloid and tau positivity earlier, to improve screen failure rates. Machine learning algorithms will also help to predict longitudinal changes in cognition, which will be useful in clinical trials to include participants whose cognition will decrease more over a shorter period of time, therefore the effects of an agent will be seen earlier. Additionally, algorithms can be implemented to study the patterns and evolution of neurodegenerative diseases in a more data driven way. This interview took place at the Clinical Trials on Alzheimer's Disease congress 2022 in San Francisco.

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