Semantically enabling pharmacogenomic data for the realization of personalized medicine

Matthias Samwald, Adrien Coulet, Iker Huerga, Robert L. Powers, Joanne S. Luciano, Robert R. Freimuth, Frederick Whipple, Elgar Pichler, Eric Prud'hommeaux, Michel Dumontier, M. Scott Marshall*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

13 Citations (Web of Science)

Abstract

Understanding how each individual's genetics and physiology influences pharmaceutical response is crucial to the realization of personalized medicine and the discovery and validation of pharmacogenomic biomarkers is key to its success. However, integration of genotype and phenotype knowledge in medical information systems remains a critical challenge. The inability to easily and accurately integrate the results of biomolecular studies with patients' medical records and clinical reports prevents us from realizing the full potential of pharmacogenomic knowledge for both drug development and clinical practice. Herein, we describe approaches using Semantic Web technologies, in which pharmacogenomic knowledge relevant to drug development and medical decision support is represented in such a way that it can be efficiently accessed both by software and human experts. We suggest that this approach increases the utility of data, and that such computational technologies will become an essential part of personalized medicine, alongside diagnostics and pharmaceutical products.
Original languageEnglish
Pages (from-to)201-212
JournalPharmacogenomics
Volume13
Issue number2
DOIs
Publication statusPublished - Jan 2012
Externally publishedYes

Keywords

  • clinical decision support systems
  • knowledge representation
  • ontologies
  • personalized medicine
  • pharmacogenomics
  • translational medicine

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