GLP-1 drugs have produced game-changing results for many patients with diabetes and obesity, but researchers at Carle Illinois College of Medicine (CI MED) are now using artificial intelligence (AI) to push diabetes treatment a step further.
A CI MED team has launched first-of-its-kind research leveraging AI to discover new drugs to fight type 2 diabetes through a triple-target approach. Student Anthony Wong and his team say their method could speed the design and discovery of new ‘triple-agonist’ drugs that improve the regulation of both blood glucose and weight.
Wong and the team – led by Dr. Kunal Patel, a CI MED clinical professor and principal investigator on the project – are breaking new ground by using AI to identify potential drug candidates that pose a triple threat to diabetes. Existing drugs for type 2 diabetes target only two receptors (GLP-1 and glucagon) to trigger hormones that control blood glucose levels and curb obesity. “We're designing ‘keys’ that can open three locks simultaneously by targeting three different hormone receptors (GLP-1, glucagon, and glucose-dependent insulinotropic polypeptide, or GIP) that work together to control blood sugar and body weight,” Wong said.
The quest to develop triple-agonist drugs for diabetes is not new, but none are currently on the market (retatrutide is in late-stage clinical trials). Identifying and developing new drugs can take years of trial and error without advanced tools like AI.
“This research could speed up the development of next-generation diabetes and obesity treatments, and reducing the time and cost of drug development could bring effective medications to patients sooner,” Wong said. “These methods could be adapted for other multi-target therapies in cancer, autoimmune diseases, and more.”
Tapping into the team’s collective expertise in medicine, computer science, and engineering, the researchers adapted an advanced AI technique that can capture the 3D shape and chemical properties of amino acid chains to help narrow the possibilities for the three-target approach. “We then combined our AI with genetic algorithms to systematically design new candidate drugs, creating 20 promising new peptide sequences (amino acids linked together in a specific order to form a chain),” Wong explained. Researchers can then target their development efforts on combinations that show the most promise.
Wong will showcase the new research before a panel of medical experts as one of five finalists in the American Medical Association’s 2025 Research Challenge competition, the largest research competition in the US for medical students, residents, and international medical graduates. More than 1400 abstracts were submitted from institutions nationwide, with only sixty selected as semifinalists. Wong will compete with four other researchers for a $10,000 grand prize in February 2026.
Earlier this year, Wong was named the Illinois Young Innovator of the Year at the Illinois Falling Walls competition in Chicago for a separate initiative to create a new obstetrical device for safer assisted deliveries. He plans to specialize in internal medicine when he enters the residency match process in March of 2026.
In addition to Dr. Patel and Wong, the team includes Dr. TC Chen, a CI MED professor and physician at Carle Health, and CI MED student Sanskruthi ‘Priya’ Guduri. [See their submitted abstract here.]