Marylyn D. Ritchie, Ph.D., FACMI, is the chief artificial intelligence officer (CAIO) for the Medical University of South Carolina (MUSC) enterprise, director of a new center for artificial intelligence (AI), as well as associate dean for Artificial Intelligence and director of the Division of Computational Health Sciences & Al in the College of Medicine at 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 (FACMI) in 2020. Dr. Ritchie was elected as a member of the National Academy of Medicine (NAM) in 2021.
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 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.