Personalized medicine: Challenges and opportunities for translational bioinformatics

Casey Lynnette Overby, Peter Tarczy-Hornoch

Research output: Contribution to journalReview articlepeer-review


Personalized medicine can be defined broadly as a model of healthcare that is predictive, personalized, preventive and participatory. Two US Presidents Council of Advisors on Science and Technology reports illustrate challenges in personalized medicine (in a 2008 report) and in use of health information technology (in a 2010 report). Translational bioinformatics is a field that can help address these challenges and is defined by the American Medical Informatics Association as "the development of storage, analytic and interpretive methods to optimize the transformation of increasing voluminous biomedical data into proactive, predictive, preventative and participatory health." This article discusses barriers to implementing genomics applications and current progress toward overcoming barriers, describes lessons learned from early experiences of institutions engaged in personalized medicine and provides example areas for translational bioinformatics research inquiry.

Original languageEnglish (US)
Pages (from-to)453-462
Number of pages10
JournalPersonalized Medicine
Issue number5
StatePublished - Jul 2013
Externally publishedYes


  • biobanks
  • clinical decision support
  • computational analyse
  • education
  • electronic health records
  • implementation challenges
  • individual research results
  • personalized medicine
  • translational bioinformatics
  • translational research

ASJC Scopus subject areas

  • Molecular Medicine
  • Pharmacology

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