Medicine

AI Tool Screens Alzheimer’s Patients for Clinical Trials More Effectively

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Alzheimer's diseaseBiomarkerClinical trial

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Researchers at the Keck School of Medicine of USC developed a blood-based screening algorithm that significantly decreased the number of unnecessary PET scans required to enroll patients at risk for Alzheimer's disease in clinical trials. The algorithm streamlines the patient screening process by using blood biomarkers to identify suitable candidates before proceeding to more expensive and time-consuming PET imaging. This approach was published in the peer-reviewed journal Alzheimer's & Dementia.


This screening tool could make Alzheimer's clinical trials more cost-effective and efficient by reducing reliance on expensive PET scans during patient recruitment. The method may accelerate drug development by enabling faster enrollment of appropriate participants while lowering overall trial costs.


A new blood-based screening algorithm dramatically reduced the number of unnecessary PET scans needed to recruit patients at risk of Alzheimer’s disease for a clinical trial, according to research from scientists at the Keck School of Medicine of USC published in the journal Alzheimer’s & Dementia.

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