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.

The model successfully predicted higher amyloid burden in AD and OTH groups, supporting its utility for improving participant selection.

While correlations with tau PET were absent—likely due to early disease stage—future work will refine thresholds and expand applicability. IXICO’s advanced imaging analytics and operational expertise enable precision recruitment, delivering measurable efficiency gains for clinical trials.

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