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Medical Xpress · September 9, 2026

Algorithmic tool may improve screening of patients for an Alzheimer's clinical trial

MedicineHealth AdministrationPharmacy
THE AI ANGLE
Algorithmic screening and risk stratification for clinical trial eligibility

Researchers at the Keck School of Medicine of USC developed a blood-based screening algorithm that reduced the rate of ineligible patients undergoing costly PET scans for the AHEAD 3-45 Alzheimer's clinical trial from over 70% to 31%. Incorporating plasma biomarkers (amyloid-beta ratio and p-tau217), age, and APOE4 status through a Mixture of Experts statistical approach, the model estimates amyloid burden across a continuous spectrum. This advancement significantly reduces financial and logistical burdens for trial sites and patients, facilitating earlier identification of candidates for disease-modifying interventions.

THE TEACHING ANGLE
Instructors can examine how using predictive algorithmic filters on accessible biomarkers can optimize clinical trial enrollment and reduce health system expenditures associated with high-cost confirmatory diagnostics like PET scans.

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