Web-scale pharmacovigilance: listening to signals from the crowd

J Am Med Inform Assoc. 2013 May 1;20(3):404-8. doi: 10.1136/amiajnl-2012-001482. Epub 2013 Mar 6.

Abstract

Adverse drug events cause substantial morbidity and mortality and are often discovered after a drug comes to market. We hypothesized that Internet users may provide early clues about adverse drug events via their online information-seeking. We conducted a large-scale study of Web search log data gathered during 2010. We pay particular attention to the specific drug pairing of paroxetine and pravastatin, whose interaction was reported to cause hyperglycemia after the time period of the online logs used in the analysis. We also examine sets of drug pairs known to be associated with hyperglycemia and those not associated with hyperglycemia. We find that anonymized signals on drug interactions can be mined from search logs. Compared to analyses of other sources such as electronic health records (EHR), logs are inexpensive to collect and mine. The results demonstrate that logs of the search activities of populations of computer users can contribute to drug safety surveillance.

MeSH terms

  • Data Mining
  • Drug Interactions
  • Drug-Related Side Effects and Adverse Reactions
  • Humans
  • Hydroxymethylglutaryl-CoA Reductase Inhibitors / adverse effects
  • Hyperglycemia / chemically induced
  • Information Storage and Retrieval / statistics & numerical data*
  • Internet*
  • Paroxetine / adverse effects
  • Pharmacovigilance*
  • Pravastatin / adverse effects
  • Product Surveillance, Postmarketing / methods*
  • ROC Curve
  • Serotonin Uptake Inhibitors / adverse effects

Substances

  • Hydroxymethylglutaryl-CoA Reductase Inhibitors
  • Serotonin Uptake Inhibitors
  • Paroxetine
  • Pravastatin