Artificial intelligence could help expand access to clinical trials for patients in rural communities, where geography and a lack of research infrastructure have historically limited opportunities to participate.
AI technology developed by Paradigm Health can screen 8,000 times more patients for potential clinical trial matches in just 10 minutes than traditional screening processes are able to do in a day, attendees at Newsweek’s AI Health Summit in New York were told.
“If you live in a rural area, your likelihood of getting access to best possible care, which could be a clinical trial, is limited,” explained Kent Thoelke, CEO of Paradigm Health. Around 81.7 million Americans – nearly a quarter of the population – live in areas classified as rural by the Federal Housing Finance Agency, yet many face significant barriers to accessing clinical trials.
Research published in JCO Oncology Practice found that 86% of nonmetropolitan U.S. counties had no active cancer treatment trials in 2022, compared with 44% of metropolitan counties. Separate research published in March 2025 by the National Library of Medicine involving nearly 30,000 cancer trial participants found that almost three-quarters of those from rural areas traveled more than 50 miles to participate, compared with 16% of urban patients.
AI could help close that gap by rapidly searching electronic health records for patients who meet complex trial eligibility criteria.
“That process manually you can screen maybe a dozen patients in a day,” Thoelke said. “We can screen 100,000 patients in 10 minutes.”
Thoelke said more than 85 percent of the health systems Paradigm works with are in community and rural areas.
He said his company has seen substantial increases in patient screening in community and rural settings after its technology is integrated with electronic health records.
“We’re going from 10,000 patients screened to 20,000 patients screened,” he said.
Furthermore, Thoelke said the system can use scheduling information to flag potential trial candidates ahead of upcoming appointments.
“If we know a patient is coming in in the next two or three weeks, that they’ve got a scan coming up, we try to surface those patients to have an appropriate conversation at the right time based on what we know about their disease state and if they match to a trial,” Thoelke said.
Jennifer Litton, a breast medical oncologist and chief clinical research officer at The University of Texas MD Anderson Cancer Center, also highlighted the potential for AI to expand where trials can reach patients.
“We’re finding ways to get trials closer to people where they are at home instead of just the folks that can get to a large academic center,” she said.
But Thoelke said technology alone cannot eliminate the barriers. Connecting health systems to the necessary infrastructure requires IT investment and legal agreements that can take months.
“For the majority of these community and rural systems, without that infrastructure, they just can’t compete at scale, and they can’t provide their patients access to those trials,” he said.
For Thoelke, the issue ultimately comes down to whether geography determines what treatment opportunities patients receive.
“If you live in rural North Dakota, you should not die because you live in rural North Dakota and can’t get to the Mayo Clinic or the Cleveland Clinic,” he said. “This allows access in those areas to therapies that those patients otherwise wouldn’t get.”