Yale University-Mayo Clinic CERSI

Project Title: Evaluation of GLP-1 FA Efficacy and Safety in Older Adults with Obesity

Dr. Chen is a postdoctoral fellow in the National Clinician Scholars Program and the Geriatric Clinical Epidemiology and Age- Related Research T32 program. She obtained her MD at the University of Texas Health Science Center in Houston. She completed her residency and chief residency in the Yale Primary Care Program in internal medicine. During her clinical training, she developed an interest in health care delivery and access, specifically for patients with obesity. Her research interests include access to primary care, the treatment of obesity in older adults, and medication cost.

Project Title: The Portrayal of Efficacy and Safety in FDA Press Releases for Novel Drug Approvals

Karthik Chetlapalli is a medical student at the Yale School of Medicine. His research interests include regulations around claims made in public and private media, clinical trial incentives and design within oncology accelerated approval, and equitable, competitive drug pricing. His CERSI Scholars project aims to study the nature of FDA press releases for drug approvals and assess quantitative versus qualitative language use when conveying drug risk and efficacy. This work has the potential to improve the quality of drug approval communications in a manner that is more accessible and readily understood by the public.

Project Title: Efficacy of Black Box Warnings: A Systematic Review

Harry Doernberg is a medical student at Yale. His clinical interests focus on the care of adults with developmental disabilities, and his research interests include meta-research and less-is-more medicine. His CERSI Scholars project evaluates the efficacy of FDA post-marking in effecting changes in prescription patterns.

Project Title: Towards an Enhanced Framework: The 'Four Targets' Approach for Generating Real-World Evidence in Medication for Opioid Use Disorder

Haidong Lu serves as an Instructor (NIDA K99 Scholar) in the Department of Internal Medicine at Yale School of Medicine and is a junior member of the Yale Program in Addiction Medicine. He is an epidemiologist and methodologist who is passionate about bridging the disciplines of epidemiology, statistics, population health and medical research. His research focuses on leveraging appropriate advanced epidemiologic methods to generate causally interpretable real-world evidence bases from observational data (e.g., electronic health records). In addition to observational studies, Dr. Lu is dedicated to enhancing methodologies for analyzing randomized controlled trials, particularly in addressing challenges related to non-compliance and generalizability. He is also interested in the burgeoning field of Artificial Intelligence (AI) for healthcare. His substantive research interests center around substance use, HIV, and pharmacoepidemiology.

Project Title: Testing Composite Endpoints with Win Ratio Method in Group Sequential Clinical Trials

Yunhan Mou is a PhD student in the Department of Biostatistics at the Yale School of Public Health. His research interests include the design and analysis of clinical trials, as well as the high-dimensional data analysis. His CERSI Scholars project focuses on the use of Win Ratio family methods in clinical trials employing group sequential design, with a particular emphasis on real-world practice.

Project Title: Evaluation of Large Language Models as Automated Deprescribing Tools in Older Patients

Vimig Socrates is a 5th year PhD Student in Computational Biology and Bioinformatics under the Section for Biomedical Informatics & Data Science. He is a member of the HarmonAI Health Lab (HAIL) lab (led by Dr. Andrew Taylor, MD, MHS). With a background in Computer Science, he is primarily interested in gaining a deeper understanding of the intersection between natural language processing methods and cognition in clinical reasoning. His previous work includes the development of language models for emergency medicine applications, including UTI symptoms and incarceration status detection. His CERSI scholar project aims to use large language models to interpret and evaluate geriatric deprescribing criteria (STOPP/Beers) on emergency room patients. The study has the potential to reduce the rate of adverse drug events to the ED, improve geriatric quality of life, and reduce the health system's overall medication burden.