10:10am Room B - Data Science in the Pursuit of Precision Medicine in Warfarin Therapy

After over 50 years in use, adverse drug events due to warfarin therapy remain a major clinical concern, with approximately 10% of users reporting adverse events. Weekly therapeutic doses of warfarin vary up to 15- fold among individuals, making it difficult to predict a patient’s therapeutic dose which may increase the number of adverse drug events seen in warfarin therapy. The field of precision medicine aims to accurately predict which therapy best fits a patient and their perfect dosing schedule to achieve the safest, most effective pharmaceutical therapy. For example, genetic and non-genetic factors are used to predict dose in algorithms that aim to alleviate adverse drug events. Recently, microbiomes of the human body have been established as additional drivers of drug response variability. Between the human genome, host microbiomes, and clinical data scraped from electronic health records, precision medicine has a surplus of data! This talk will highlight data science methods employed within the field of precision medicine.

Heidi Steiner, PSM

Senior Research Scientist
Data Science Educator
Data Science Institute
University of Arizona


Heidi Steiner is a Data Science Educator at UArizona's Data Science Institute. She is working on her dissertation research at the College of Medicine - Tucson, where she is focused on understanding the inter-variability in anticoagulant dosing. Heidi loves R programming, especially the tidyverse, data visualization and reproducible reporting.