Document Detail


Semantically enabling pharmacogenomic data for the realization of personalized medicine.
MedLine Citation:
PMID:  22256869     Owner:  NLM     Status:  In-Data-Review    
Abstract/OtherAbstract:
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.
Authors:
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
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Pharmacogenomics     Volume:  13     ISSN:  1744-8042     ISO Abbreviation:  Pharmacogenomics     Publication Date:  2012 Jan 
Date Detail:
Created Date:  2012-01-19     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  100897350     Medline TA:  Pharmacogenomics     Country:  England    
Other Details:
Languages:  eng     Pagination:  201-12     Citation Subset:  IM    
Affiliation:
Section for Medical Expert & Knowledge-Based Systems, Center for Medical Statistics, Informatics, & Intelligent Systems, Medical University of Vienna, Spitalgasse 23, A-1090 Vienna, Austria and Institute of Software Technology & Interactive Systems, University of Technology Vienna, Favoritenstrasse 9-11/188, A-1040 Vienna, Austria.
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