Automatic detection of drug interaction mismatches in package inserts

Majid Rastegar-Mojarad, Brian Harrington, Steven M. Belknap

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

The US Code of Federal Regulation (21 CFR 207) mandates that pharmaceutical manufacturers submit their FDA-approved drug information as medication Package Insert (PI). PI should provide comprehensive, current, and accurate information about the medical use of a drug. However, PI narratives are cumbersome for healthcare providers to navigate and are therefore rarely used by them. We are developing Paracelsus, a tool for automatically extracting structured drug information from PI. Paracelsus has the potential to allow healthcare providers to benefit from the rich drug information in PI for patient care. In this study, we report the development and evaluation of Paracelsus on drug-drug interactions. We show that Paracelsus performs with a high accuracy, discovering interactions not covered by other medical compendia, and in addition automatically detecting inconsistencies in the package inserts.

Original languageEnglish (US)
Title of host publicationProceedings of the 2013 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2013
Pages373-377
Number of pages5
DOIs
StatePublished - Dec 1 2013
Event2013 2nd International Conference on Advances in Computing, Communications and Informatics, ICACCI 2013 - Mysore, India
Duration: Aug 22 2013Aug 25 2013

Publication series

NameProceedings of the 2013 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2013

Other

Other2013 2nd International Conference on Advances in Computing, Communications and Informatics, ICACCI 2013
CountryIndia
CityMysore
Period8/22/138/25/13

Keywords

  • Drug-Drug interaction
  • Package Insert
  • information retrival

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems

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