journal articles
AI-AUGMENTED FRAMEWORKS FOR ENHANCING ALZHEIMER’S DISEASE CLINICAL TRIALS: A MEMORY CLINIC PERSPECTIVE
Francesco K. Yigamawano, Aubrey R. Odom, Chonghua Xue, Hemant K. Pandey, Vijaya B. Kolachalama
J Prev Alz Dis 2026;1(13)
Alzheimer’s disease (AD) clinical trials continue to face major hurdles in patient identification, resulting in delayed timelines, underpowered studies, and escalating costs. This perspective explores these challenges through the lens of a memory clinic, where hundreds of cases often translate into only a handful of enrollments. We highlight the potential of artificial intelligence (AI) to address this gap by powering chatbots for awareness and pre-screening, decision support tools for case identification, and algorithms for matching patients to trial-specific criteria, automating and streamlining the recruitment process. We also examine critical considerations in developing such AI-driven tools, including data standardization, privacy protections, and ethical safeguards. With thoughtful implementation, these innovations could accelerate more inclusive and efficient AD trials, ultimately bringing therapies to patients faster.
CITATION:
Francesco K. Yigamawano ; Aubrey R. Odom ; Chonghua Xue ; Hemant K. Pandey ; Vijaya B. Kolachalama (2025): AI-augmented frameworks for enhancing Alzheimer’s disease clinical trials: A memory clinic perspective Author links open overlay panel. The Journal of Prevention of Alzheimer’s Disease (JPAD). https://doi.org/10.1016/j.tjpad.2025.1003968