Public Biography
Dr. Marylyn D. Ritchie is the Chief Artificial Intelligence Officer for the MUSC Enterprise, Director of the MUSC AI Center for Health Innovation and Informatics, as well as Associate Dean for Artificial Intelligence and Director of the Division of Computational Health Sciences and Al in the College of Medicine at the Medical University of South Carolina (MUSC). Dr. Ritchie is also the SmartState Endowed Chair in Translational Biomedical Informatics. Dr. Ritchie is an expert in translational bioinformatics, with a focus on developing, applying, and disseminating algorithms, methods, and tools integrating electronic health records (EHR) with genomics. Dr. Ritchie has over 20 years of experience in translational bioinformatics and has authored over 500 publications. Dr. Ritchie was appointed as a Fellow of the American College of Medical Informatics (ACMI) in 2020. Dr. Ritchie was elected as a member of the National Academy of Medicine in 2021. Dr. Ritchie was a member of the ELAM class of 2022. Dr. Ritchie served as a member of the AMIA Board of Directors in 2025-2026.
In her new role, Dr. Ritchie is developing the AI strategy across MUSC. She is leading enterprise-wide strategies to harness AI in support of the institution’s tripartite mission of education, research, and patient care. She is focused on building collaborative AI initiatives that connect clinicians, faculty, industry partners, staff, students, and trainees to drive innovation at MUSC.
The mission of Dr. Ritchie’s research program is to improve our understanding of the underlying architecture of common, complex diseases. They develop and apply a breadth of translational bioinformatics approaches to explore the genome, the phenome, and the exposome. The approaches involve the development and application of new statistical, computational, machine learning, and Artificial Intelligence (AI) methods with a focus on embracing complexity to uncover relationships between multi-omics data, clinical data (mostly from electronic health records), environmental exposures, and social determinants of health. These meta-dimensional approaches hold the promise of providing a more comprehensive view of genetic, genomic, and phenotypic information.
Dr. Ritchie is also interested in implementation of precision medicine into routine clinical care. Throughout her career, she has participated in research programs focused on the implementation of both pharmacogenomics and genomic medicine. Recent efforts are enriched in the concept of the Learning Health System, whereby they leverage the electronic health record linked biobank as a living laboratory to conduct research and then implement the findings to improve clinical care.
In her new role, Dr. Ritchie is developing the AI strategy across MUSC. She is leading enterprise-wide strategies to harness AI in support of the institution’s tripartite mission of education, research, and patient care. She is focused on building collaborative AI initiatives that connect clinicians, faculty, industry partners, staff, students, and trainees to drive innovation at MUSC.
The mission of Dr. Ritchie’s research program is to improve our understanding of the underlying architecture of common, complex diseases. They develop and apply a breadth of translational bioinformatics approaches to explore the genome, the phenome, and the exposome. The approaches involve the development and application of new statistical, computational, machine learning, and Artificial Intelligence (AI) methods with a focus on embracing complexity to uncover relationships between multi-omics data, clinical data (mostly from electronic health records), environmental exposures, and social determinants of health. These meta-dimensional approaches hold the promise of providing a more comprehensive view of genetic, genomic, and phenotypic information.
Dr. Ritchie is also interested in implementation of precision medicine into routine clinical care. Throughout her career, she has participated in research programs focused on the implementation of both pharmacogenomics and genomic medicine. Recent efforts are enriched in the concept of the Learning Health System, whereby they leverage the electronic health record linked biobank as a living laboratory to conduct research and then implement the findings to improve clinical care.
Historic ACMI Biography
Dr. Marylyn Ritchie is a translational bioinformatician and pioneer in the integration and Computational analysis of genomics data and clinical data from EHRs. She published some of the first papers showing that genetic associations could be discovered and validated using EHR-derived phenotypes. She also co-invented the phenome-wide association study (PheWAS).
Affiliations
The American College of Medical Informatics
ACMI is a college of elected Fellows from the U.S. and abroad who have made significant and sustained contributions to the field of medical informatics. It is the central body for a community of scholars and practitioners who are committed to advancing the informatics field.
Year Elected
2020