Blood-based Algorithm Cuts PET Scans for Alzheimer’s Trial Recruitment

A team of researchers at the Keck School of Medicine of USC has developed a blood‑based screening algorithm that markedly cuts the number of unnecessary positron emission tomography (PET) scans required to identify patients at risk of Alzheimer’s disease for clinical trials. The study, published in the journal *Alzheimer’s & Dementia*, demonstrates that the algorithm can accurately flag individuals who are likely to exhibit amyloid pathology, thereby streamlining the recruitment process for early‑stage therapeutic studies.

The new approach leverages a panel of blood biomarkers to predict amyloid burden, which is traditionally confirmed through costly and invasive PET imaging. By reducing the need for PET scans, the algorithm not only lowers screening costs but also lessens patient burden and accelerates the pace at which suitable participants can be enrolled. The findings suggest that large‑scale trials could achieve faster enrollment timelines while maintaining rigorous diagnostic standards.

These results underscore the growing role of liquid biopsy techniques in neurodegenerative disease research. If adopted broadly, the blood‑based screening tool could transform clinical trial design, enabling more efficient evaluation of emerging Alzheimer’s therapies and ultimately expediting the delivery of effective treatments to patients.