Generative AI for Clinical Trial Development
Speaker
Jimeng Sun
Carle Illinois College of Medicine at University of Illinois Urbana Champaign
Host
Marzyeh Ghassemi
IMES, CSAIL, EECS
Abstract:
We present three recent papers on how Generative AI can help clinical trial development:
TrialGPT: Matching Patients to Clinical Trials Recruiting the right patients quickly can be challenging in clinical trials. TrialGPT uses Large Language Models (LLMs) to predict a patient’s suitability for various trials based on their medical notes, making it easier to find the best match.
AutoTrial: Improving Clinical Trial Eligibility Criteria Design Designing eligibility criteria for clinical trials can be complex. AutoTrial uses language models to streamline this process. It combines targeted generation, adapts to new information, and clearly explains its decisions.
MediTab: Handling Diverse Clinical Trial Data Tables Medical data, such as clinical trial results, comes in various tables, making it hard to compare and combine. MediTab uses LLMs to merge different data tables and align unfamiliar data to ensure consistency and accuracy.
Bio:
Dr. Sun is a Health Innovation Professor at the Computer Science Department and Carle Illinois College of Medicine at University of Illinois Urbana Champaign. Previously, he was an associate professor at Georgia Tech's College of Computing and co-directed the Center for Health Analytics and Informatics. Dr. Sun's research focuses on using artificial intelligence (AI) to improve healthcare. This includes deep learning for drug discovery, clinical trial optimization, computational phenotyping, clinical predictive modeling, treatment recommendation, and health monitoring. He has been recognized as one of the Top 100 AI Leaders in Drug Discovery and Advanced Healthcare. Dr. Sun has published over 300 papers with over 25,000 citations, and h-index 81. He collaborates with leading hospitals such as MGH, Beth Israel Deaconess, OSF healthcare, Northwestern, Sutter Health, Vanderbilt, Northwestern, Geisinger, and Emory, as well as the biomedical industry, including IQVIA, Medidata and multiple pharmaceutical companies. Dr. Sun earned his B.S. and M.Phil. in computer science at Hong Kong University of Science and Technology, and his Ph.D. in computer science at Carnegie Mellon University.
We present three recent papers on how Generative AI can help clinical trial development:
TrialGPT: Matching Patients to Clinical Trials Recruiting the right patients quickly can be challenging in clinical trials. TrialGPT uses Large Language Models (LLMs) to predict a patient’s suitability for various trials based on their medical notes, making it easier to find the best match.
AutoTrial: Improving Clinical Trial Eligibility Criteria Design Designing eligibility criteria for clinical trials can be complex. AutoTrial uses language models to streamline this process. It combines targeted generation, adapts to new information, and clearly explains its decisions.
MediTab: Handling Diverse Clinical Trial Data Tables Medical data, such as clinical trial results, comes in various tables, making it hard to compare and combine. MediTab uses LLMs to merge different data tables and align unfamiliar data to ensure consistency and accuracy.
Bio:
Dr. Sun is a Health Innovation Professor at the Computer Science Department and Carle Illinois College of Medicine at University of Illinois Urbana Champaign. Previously, he was an associate professor at Georgia Tech's College of Computing and co-directed the Center for Health Analytics and Informatics. Dr. Sun's research focuses on using artificial intelligence (AI) to improve healthcare. This includes deep learning for drug discovery, clinical trial optimization, computational phenotyping, clinical predictive modeling, treatment recommendation, and health monitoring. He has been recognized as one of the Top 100 AI Leaders in Drug Discovery and Advanced Healthcare. Dr. Sun has published over 300 papers with over 25,000 citations, and h-index 81. He collaborates with leading hospitals such as MGH, Beth Israel Deaconess, OSF healthcare, Northwestern, Sutter Health, Vanderbilt, Northwestern, Geisinger, and Emory, as well as the biomedical industry, including IQVIA, Medidata and multiple pharmaceutical companies. Dr. Sun earned his B.S. and M.Phil. in computer science at Hong Kong University of Science and Technology, and his Ph.D. in computer science at Carnegie Mellon University.