Text Mining for Pharmacovigilance and Drug Safety


Tracking and reporting adverse events
In recent years, regulatory authorities such as the FDA and EMA have placed an increased emphasis on drug safety of marketed products, particularly the tracking and reporting of adverse events. Pharmaceutical companies are expected to regularly screen the worldwide scientific literature for potential adverse drug reactions, at least every two weeks. The use of text mining and other tools to streamline the literature review process for pharmacovigilance is more crucial than ever in order to ensure patient safety, without overloading drug safety teams.
Manual review of adverse events is time-consuming
Eric Lewis (Safety Development Leader at GlaxoSmithKline) talked at the Linguamatics Text Mining Summit about the challenges of reviewing medical literature for safety signals. For example, he looked for literature for a sample of just 20 marketed products across a 300-day period. Eric found that there were on average 60 new references per day (with a total of over 11,000 documents). He found that manual review time was 1.2 to 1.6 minutes per abstract. He extrapolated this to a typical pharma company product portfolio of 200 marketed products, and showed that this volume of literature would take over 2,200 hours to review – hugely time-consuming.