Cameron Thomas

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Clinical and Administrative Pharmacy, Athens Assistant Professor

Dr. Cameron D. Thomas, PharmD, PhD, is an Assistant Professor in the Department of Clinical & Administrative Pharmacy at the University of Georgia and a Faculty Fellow in the AI Department. He earned his PharmD from the University of Florida, followed by a PGY-1 Clinical Pharmacy residency at UF Health Jacksonville and a PGY-2 Clinical Pharmacogenetics residency at St. Jude Children’s Research Hospital. He later completed his PhD at the University of Florida, focusing on precision medicine approaches to antiplatelet therapy following percutaneous coronary intervention.

Dr. Thomas’ research integrates pharmacogenomics, clinical risk stratification, and artificial intelligence to improve patient outcomes across multiple therapeutic areas. His work applies machine learning and natural language processing (NLP) to analyze electronic health records, extract and annotate clinical events, and develop predictive models for adverse drug outcomes. In cardiovascular medicine, he has advanced CYP2C19-guided P2Y12 inhibitor selection and clinical-genetic risk tools to optimize dual antiplatelet therapy. Overall, his research seeks to personalize pharmacotherapy through data-driven methods that balance efficacy and safety in patient care.

Education:
  • Doctor of Philosophy, University of Florida, 2025
  • NHGRI T32 PARADIGM Fellowship in Genomic Medicine, University of Florida, 2021
  • PGY-2 Clinical Pharmacogenetics Residency, St. Jude Children’s Research Hospital, 2018
  • PGY-1 Pharmacy Residency, UF Health Jacksonville, 2017
  • Doctor of Pharmacy, University of Florida, 2016
  • Associate of Arts, Florida Gateway College, 2012
Research Interests:
  • Pharmacogenomics and precision medicine
  • Clinical risk stratification and outcome prediction
  • Artificial intelligence applications in pharmacotherapy
  • Machine learning and natural language processing (NLP) for electronic health records
  • Adverse drug event detection and prediction
  • Data-driven optimization of cardiovascular drug therapy