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Overby CL, Tarczy-Hornoch P. Personalized medicine: challenges and opportunities for translational bioinformatics. Per Med. 2013;10(5):453-462doi: 10.2217/pme.13.30.
Overby, C. L., & Tarczy-Hornoch, P. (2013). Personalized medicine: challenges and opportunities for translational bioinformatics. Personalized medicine, 10(5), 453-462. https://doi.org/10.2217/pme.13.30
Overby, Casey Lynnette, and Tarczy-Hornoch, Peter. "Personalized medicine: challenges and opportunities for translational bioinformatics." Personalized medicine vol. 10,5 (2013): 453-462. doi: https://doi.org/10.2217/pme.13.30
Overby CL, Tarczy-Hornoch P. Personalized medicine: challenges and opportunities for translational bioinformatics. Per Med. 2013 Jul 01;10(5):453-462. doi: 10.2217/pme.13.30. PMID: 24039624; PMCID: PMC3770190.
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Per Med. 2013 Jul 01;10(5):453-462. doi: 10.2217/pme.13.30.

Personalized medicine: challenges and opportunities for translational bioinformatics.

Personalized medicine

Casey Lynnette Overby, Peter Tarczy-Hornoch

Affiliations

  1. Program in Personalized & Genomic Medicine and Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA.

PMID: 24039624 PMCID: PMC3770190 DOI: 10.2217/pme.13.30

Abstract

Personalized medicine can be defined broadly as a model of healthcare that is predictive, personalized, preventive and participatory. Two US President's 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.

Keywords: biobanks; clinical decision support; computational analyses; education; electronic health records; implementation challenges; individual research results; personalized medicine; translational bioinformatics; translational research

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