LAUSR

The main objective of this project was to introduce approaches for comprehensive medication risk assessment in people with polypharmacy that simultaneously account for multiple drug and gene effects. To achieve this goal, we developed an integrated knowledge repository of actionable pharmacogenes and a scoring algorithm that was pilot-tested using a data set containing pharmacogenomic information of people with polypharmacy. Metabolic phenotyping using resulting database demonstrated recall of 83.6% and precision of 87.1%. The final scoring algorithm yielded medication risk scores that allowed distinguish frequently hospitalized older adults with polypharmacy and older adults with polypharmacy with low hospitalization rate (average scores respectively: 75.89±15.45 and 10.51±1.82, p<0.05). The initial prototype assessment demonstrated feasibility of our approach and identified steps for improving risk scoring algorithms. Pharmacogenomics-driven medication risk assessment in patient with polypharmacy has potential in identifying inadequate drug regimens and preventing adverse drug events.