Agentic AI May Help Close Gaps in Clinical Trial Enrollment

Access to clinical trials can vary significantly depending on where patients receive care, with distance, available research infrastructure, and referral pathways among the factors that can influence enrollment. In an interview with Targeted Oncology^TM, Shaalan Beg, MD, MBA, FASCO, of ConcertAI, discusses how artificial intelligence (AI)-enabled clinical trial screening could help extend research opportunities to patients receiving care in community settings.

Beg highlights the growing role of community and satellite sites in clinical research and the challenge of ensuring that patients seen outside major academic centers have the same opportunities to be identified for appropriate trials. AI tools could help research teams extend screening capabilities across these sites, allowing potentially eligible patients to be identified closer to where they receive care.

The potential impact extends beyond academic vs community settings. Clinical trial participation can also be influenced by factors such as insurance status, geography, and the distance a patient must travel to a trial site. By helping community oncology practices identify and evaluate potential trial candidates locally, AI could reduce some of the logistical barriers that can prevent patients from participating in research.