Events
Leveraging AI to Improve Oncology Trial Design: Digital Twins, Trial Matching, and Trial Emulation
The Institute of Artificial Intelligence for Digital Health invites you to attend its monthly seminar series, which will feature Dr. Ravi Parikh, an associate professor of Hematology and Medical Oncology at the Emory University School of Medicine and medical director of the Data and Technology Applications Shared Resource at Winship Cancer Institute of Emory University.
Recent advancements in artificial intelligence offer opportunities to enhance efficiency, inclusivity, and effectiveness of oncology clinical trials. This presentation explores three AI applications that Dr. Parikh and his team have been exploring in their lab to optimize cancer research design: digital twins leveraging causal inference methods to simulate treatment responses and optimize trial protocols; LLM-based trial matching systems that connect patients with appropriate studies based on molecular profiles and clinical characteristics; and machine learning trial emulation techniques that leverage real-world data to inform generalizability of traditional randomized controlled trials. By integrating these and other AI-driven approaches, researchers can design more adaptive trials, reduce costs, accelerate drug development timelines, and ultimately deliver more personalized cancer treatments.
Speaker Bio
Dr. Ravi Parikh, MD, MPP is an associate professor of Hematology and Medical Oncology at the Emory University School of Medicine and medical director of the Data and Technology Applications Shared Resource at Winship Cancer Institute of Emory University. In this role, he is responsible for its overall strategic scientific management and operational oversight. Dr. Parikh directs the Human-Algorithm Collaboration Lab, an NIH-funded multidisciplinary laboratory focusing on developing and testing algorithm-driven interventions in cancer care and serious illness, and serves on the Board of the Coalition to Transform Advanced Care (C-TAC).