Problems, challenges and promises: perspectives on precision medicine

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Title: Problems, challenges and promises: perspectives on precision medicine
Authors: Duffy, David J.
Permanent link: http://hdl.handle.net/10197/7543
Date: Aug-2015
Abstract: The 'precision medicine (systems medicine)' concept promises to achieve a shift to future healthcare systems with a more proactive and predictive approach to medicine, where the emphasis is on disease prevention rather than the treatment of symptoms. The individualization of treatment for each patient will be at the centre of this approach, with all of a patient’s medical data being computationally integrated and accessible. Precision medicine is being rapidly embraced by biomedical researchers, pioneering clinicians and scientific funding programmes in both the European Union (EU) and USA. Precision medicine is a key component of both Horizon 2020 (the EU Framework Programme for Research and Innovation) and the White House’s Precision Medicine Initiative. Precision medicine promises to revolutionize patient care and treatment decisions. However, the participants in precision medicine are faced with a considerable central challenge. Greater volumes of data from a wider variety of sources are being generated and analysed than ever before; yet, this heterogeneous information must be integrated and incorporated into personalized predictive models, the output of which must be intelligible to non-computationally trained clinicians. Drawing primarily from the field of ‘oncology’, this article will introduce key concepts and challenges of precision medicine and some of the approaches currently being implemented to overcome these challenges. Finally, this article also covers the criticisms of precision medicine overpromising on its potential to transform patient care.
Funding Details: European Commission - Seventh Framework Programme (FP7)
Science Foundation Ireland
Type of material: Journal Article
Publisher: Oxford University Press
Copyright (published version): 2015 the Author
Keywords: Systems medicine;Personalised medicine;P4 medicine;Mechanistic modelling;Computational modelling;Omic integration
DOI: 10.1093/bib/bbv060
Language: en
Status of Item: Peer reviewed
Appears in Collections:SBI Research Collection

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