AI-augmented frameworks for enhancing Alzheimer's disease clinical trials: A memory clinic perspective

Area of Science:

• Neurology
• Medical Informatics

Background:

• Alzheimer's disease (AD) clinical trials face significant patient recruitment challenges.
• These challenges lead to delayed timelines, underpowered studies, and increased costs.

Purpose of the Study:

• To explore the potential of artificial intelligence (AI) in overcoming patient identification hurdles in AD clinical trials.
• To examine the implementation considerations for AI-driven recruitment tools.

Main Methods:

• Perspective piece analyzing challenges from a memory clinic viewpoint.
• Discussion of AI applications including chatbots, decision support, and matching algorithms.
• Examination of data standardization, privacy, and ethical considerations.

Main Results:

• AI offers solutions for awareness, pre-screening, and patient-trial matching.
• Streamlining recruitment processes through AI automation is feasible.
• Critical considerations for AI tool development include data, privacy, and ethics.

Conclusions:

• AI has the potential to accelerate inclusive and efficient AD clinical trials.
• Thoughtful implementation of AI can expedite the delivery of therapies to patients.
• AI can help overcome major recruitment hurdles in Alzheimer's research.