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  IT Future of Medicine: from molecular analysis to clinical diagnosis and improved treatment

Zazzu, V., Regierer, B., Kühn, A., Sudbrak, R., & Lehrach, H. (2013). IT Future of Medicine: from molecular analysis to clinical diagnosis and improved treatment. New Biotechnology, 30(4), 362-365. doi:10.1016/j.nbt.2012.11.002.

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Zazzu, Valeria1, Author           
Regierer, Babette1, Author           
Kühn, Alexander2, 3, Author           
Sudbrak, Ralf1, Author           
Lehrach, Hans1, Author           
Affiliations:
1Dept. of Vertebrate Genomics (Head: Hans Lehrach), Max Planck Institute for Molecular Genetics, Max Planck Society, Berlin, Germany, ou_1433550              
2Systems Biology (Christoph Wierling), Dept. of Vertebrate Genomics (Head: Hans Lehrach), Max Planck Institute for Molecular Genetics, Max Planck Society, Berlin, Germany, ou_1479656              
3Alacris Theranostics GmbH, Berlin, Germany, ou_persistent22              

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 Abstract: The IT Future of Medicine (ITFoM, http://www.itfom.eu/) initiative will produce computational models of individuals to enable the prediction of their future health risks, progression of diseases and selection and efficacy of treatments while minimising side effects. To be able to move our health care system to treat patients as individuals rather than as members of larger, divergent groups, the ITFoM initiative, proposes to integrate molecular, physiological and anatomical data of every person in 'virtual patient' models. The establishment of such 'virtual patient' models is now possible due to the enormous progress in analytical techniques, particularly in the '-omics' technology areas and in imaging, as well as in sensor technologies, but also due to the immense developments in the ICT field. As one of six Future and Emerging Technologies (FET) Flagship Pilot Projects funded by the European Commission, ITFoM with more than 150 academic and industrial partners from 34 countries, will foster the development in functional genomics and computer technologies to generate 'virtual patient' models to make them available for clinical application. The increase in the capacity of next generation sequencing systems will enable the high-throughput analysis of a large number of individuals generating huge amounts of genome, epigenome and transcriptome data, but making it feasible to apply deep sequencing in the clinic to characterise not only the patient's genome, but also individual samples, for example, from tumours. The genome profile will be integrated with proteome and metabolome information generated via new powerful chromatography, mass spectrometry and nuclear magnetic resonance techniques. The individualised model will not only enable the analysis of the current situation, but will allow the prediction of the response of the patient to different therapy options or intolerance for certain drugs.

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Language(s): eng - English
 Dates: 2012-11-162013-05-25
 Publication Status: Issued
 Pages: 4
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 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1016/j.nbt.2012.11.002
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Title: New Biotechnology
Source Genre: Journal
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Publ. Info: Amsterdam et al : Elsevier
Pages: 4 Volume / Issue: 30 (4) Sequence Number: - Start / End Page: 362 - 365 Identifier: -