Toward semantic modeling of pharmacogenomic knowledge for clinical and translational decision support

The purpose of this paper is to describe pilot work on a semantic model of the pharmacogenomics information found in drug product labels. The model's development is driven by a series of use cases that we have developed to demonstrate how structured pharmacogenomics information could be more effectively used to support clinical and translational efforts. Using an iterative process, the semantic model was field-tested by five pharmacists, who used it to manually annotate a subset of the sections that the Food and Drug Administration's Table of Pharmacogenomic Biomarkers in Drug Labels cites as containing pharmacogenomics information. The five pharmacists identified a total of 213 pharmacogenomics statements in 29 sections. The model showed the potential to make the unstructured pharmacogenomic information currently written in product labeling more accessible and actionable through structured annotations of pharmacogenomics effects and clinical recommendations.