Stanford University
300 Pasteur Drive, Stanford, CA 94304
USA
Presenter: Rainer Winnenburg, PhD
Postdoctoral Scholar, BMIR
Stanford University
About the Event:
In this talk, I will present recent progress in our attempt to apply Enrichment Analysis (EA) for pharmacovigilance. EA is a technique commonly used for identifying sets of genes that are over-represented in gene expression assays based on their annotation with terms from the gene ontology (GO). Here we use a generalized version of EA to identify significant associations between marketed drugs and adverse events from the biomedical literature (MEDLINE) to assist drug safety monitoring efforts. We assess how defining a selection of adverse event terms from MeSH, based on information content, can improve the detection of adverse events for drugs and drug classes.
In the second part of my talk, I will present a project in which we aim to leverage information from electronic medical records (EMR) to reduce the adverse drug event burden caused by polypharmacy. Several studies have shown that in some cases combinations of one drug with certain drugs from another drug class can lead to an increased risk of severe adverse events (ADEs) due to unintended drug-drug interactions (DDIs) while combinations with other drugs from the same class are not associated with an increased risk. We are currently working on an approach to detect ADE signals from clinical notes in EMRs in STRIDE (Stanford Translational Research Integrated Database Environment) that inform treatment adjustments for cohorts of patients concomitantly taking drugs from different drug classes with the goal of minimizing adverse effects and maximizing efficacy.