Biomedical Data Science Seminar Series, BRB Gaulton Auditorium

Title: Groundwork for precision medicine: The role of electronic health records in discoveries and clinical implementation

This week hosted by IBI – invited by Marylyn Ritchie , PhD

Abstract: In this talk, Dr. Verma will present her work on the use of different EHR-based phenotypes, such as clinical laboratory measures, for conducting association studies to examine the interplay between genes that may contribute to the development and progression of diseases and will further discuss how these discoveries are valuable in disease risk prediction in the PMBB population.  Dr. Verma will highlight and present recent work using PMBB and other large datasets for diseases specific to females. She will also discuss current challenges with EHR phenotypes for high throughput association studies. She aims to extend the integration of EHR-based phenotyping to imaging and digital health phenotypes, allowing her to develop system genomics approaches for modeling disease complexity by linking quantitative characteristics of diseases with genetic contributors. Thus, enabling predictive modeling from integrated clinical data.

Bio: Dr. Shefali Setia Verma, Ph.D., is an Instructor in the Department of Pathology and Laboratory Medicine. As a biomedical and computational geneticist, she has expertise in developing and implementing statistical methods and tools to model the underlying genetic mechanisms of complex human diseases. Through her work on harnessing electronic health record (EHR) data for understanding the genetic underpinnings of common diseases, Dr. Verma has conducted multiple studies to determine the associations between specific genetic variations and diseases and has shown the utility of EHR-linked biobanks for discoveries in understanding disease mechanisms. Her work has resulted in more than 60 peer-reviewed research and review articles. She has also been an integral part of the Penn Medicine BioBank (PMBB) team since joining Penn, and her work has highlighted the use of EHR for delivering results back to patients. Since starting her lab in the Department of Pathology and Laboratory Medicine, Dr. Verma’s work has focused on developing EHR-based algorithms for discovering and clinical implementation of diseases unique to females. Dr. Verma describes her vision as developing automated statistical models for providing precision medicine in day-to-day clinical practice for the next-generations’ of healthcare.