Collaborative Biomedicine in the Age of Big Data: The Case of Cancer
Identifieur interne : 000256 ( Pmc/Curation ); précédent : 000255; suivant : 000257Collaborative Biomedicine in the Age of Big Data: The Case of Cancer
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- Journal of Medical Internet Research [ 1439-4456 ] ; 2014.
Abstract
Biomedicine is undergoing a revolution driven by high throughput and connective computing that is transforming medical research and practice. Using oncology as an example, the speed and capacity of genomic sequencing technologies is advancing the utility of individual genetic profiles for anticipating risk and targeting therapeutics. The goal is to enable an era of “P4” medicine that will become increasingly more predictive, personalized, preemptive, and participative over time. This vision hinges on leveraging potentially innovative and disruptive technologies in medicine to accelerate discovery and to reorient clinical practice for patient-centered care. Based on a panel discussion at the Medicine 2.0 conference in Boston with representatives from the National Cancer Institute, Moffitt Cancer Center, and Stanford University School of Medicine, this paper explores how emerging sociotechnical frameworks, informatics platforms, and health-related policy can be used to encourage data liquidity and innovation. This builds on the Institute of Medicine’s vision for a “rapid learning health care system” to enable an open source, population-based approach to cancer prevention and control.
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DOI: 10.2196/jmir.2496
PubMed: 24711045
PubMed Central: 4004150
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<front><div type="abstract" xml:lang="en"><p>Biomedicine is undergoing a revolution driven by high throughput and connective computing that is transforming medical research and practice. Using oncology as an example, the speed and capacity of genomic sequencing technologies is advancing the utility of individual genetic profiles for anticipating risk and targeting therapeutics. The goal is to enable an era of “P4” medicine that will become increasingly more predictive, personalized, preemptive, and participative over time. This vision hinges on leveraging potentially innovative and disruptive technologies in medicine to accelerate discovery and to reorient clinical practice for patient-centered care. Based on a panel discussion at the Medicine 2.0 conference in Boston with representatives from the National Cancer Institute, Moffitt Cancer Center, and Stanford University School of Medicine, this paper explores how emerging sociotechnical frameworks, informatics platforms, and health-related policy can be used to encourage data liquidity and innovation. This builds on the Institute of Medicine’s vision for a “rapid learning health care system” to enable an open source, population-based approach to cancer prevention and control.</p>
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<pmc article-type="letter"><pmc-dir>properties open_access</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-ta">J Med Internet Res</journal-id>
<journal-id journal-id-type="publisher-id">JMIR</journal-id>
<journal-title-group><journal-title>Journal of Medical Internet Research</journal-title>
</journal-title-group>
<issn pub-type="ppub">1439-4456</issn>
<issn pub-type="epub">1438-8871</issn>
<publisher><publisher-name>JMIR Publications Inc.</publisher-name>
<publisher-loc>Toronto, Canada</publisher-loc>
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<article-meta><article-id pub-id-type="pmid">24711045</article-id>
<article-id pub-id-type="pmc">4004150</article-id>
<article-id pub-id-type="publisher-id">v16i4e101</article-id>
<article-id pub-id-type="doi">10.2196/jmir.2496</article-id>
<article-categories><subj-group subj-group-type="heading"><subject>Viewpoint</subject>
</subj-group>
<subj-group subj-group-type="article-type"><subject>Viewpoint</subject>
</subj-group>
</article-categories>
<title-group><article-title>Collaborative Biomedicine in the Age of Big Data: The Case of Cancer</article-title>
</title-group>
<contrib-group><contrib contrib-type="editor"><name><surname>Eysenbach</surname>
<given-names>Gunther</given-names>
</name>
</contrib>
</contrib-group>
<contrib-group><contrib contrib-type="reviewer"><name><surname>Toldo</surname>
<given-names>Luca</given-names>
</name>
</contrib>
<contrib contrib-type="reviewer"><name><surname>Zhu</surname>
<given-names>Yue</given-names>
</name>
</contrib>
</contrib-group>
<contrib-group><contrib id="contrib1" contrib-type="author" corresp="yes"><name><surname>Shaikh</surname>
<given-names>Abdul R</given-names>
</name>
<degrees>MHSc, PhD</degrees>
<xref ref-type="aff" rid="aff1">1</xref>
<address><institution>PricewaterhouseCoopers LLP</institution>
<addr-line>1800 Tysons Boulevard</addr-line>
<addr-line>McLean, VA, 22102</addr-line>
<country>United States</country>
<phone>1 301 448 0057</phone>
<fax>1 416 340 3200</fax>
<email>shaikh@us.pwc.com</email>
</address>
</contrib>
<contrib id="contrib2" contrib-type="author"><name><surname>Butte</surname>
<given-names>Atul J</given-names>
</name>
<degrees>MD, PhD</degrees>
<xref ref-type="aff" rid="aff2">2</xref>
</contrib>
<contrib id="contrib3" contrib-type="author"><name><surname>Schully</surname>
<given-names>Sheri D</given-names>
</name>
<degrees>PhD</degrees>
<xref ref-type="aff" rid="aff3">3</xref>
</contrib>
<contrib id="contrib4" contrib-type="author"><name><surname>Dalton</surname>
<given-names>William S</given-names>
</name>
<degrees>MD, PhD</degrees>
<xref ref-type="aff" rid="aff4">4</xref>
</contrib>
<contrib id="contrib5" contrib-type="author"><name><surname>Khoury</surname>
<given-names>Muin J</given-names>
</name>
<degrees>MD, PhD</degrees>
<xref ref-type="aff" rid="aff3">3</xref>
</contrib>
<contrib id="contrib6" contrib-type="author"><name><surname>Hesse</surname>
<given-names>Bradford W</given-names>
</name>
<degrees>PhD</degrees>
<xref ref-type="aff" rid="aff3">3</xref>
</contrib>
</contrib-group>
<aff id="aff1"><sup>1</sup>
<institution>PricewaterhouseCoopers LLP</institution>
<addr-line>McLean, VA</addr-line>
<country>United States</country>
</aff>
<aff id="aff2"><sup>2</sup>
<institution>Division of Systems Medicine</institution>
<institution>Department of Pediatrics</institution>
<institution>Stanford University School of Medicine</institution>
<addr-line>Stanford, CA</addr-line>
<country>United States</country>
</aff>
<aff id="aff3"><sup>3</sup>
<institution>Division of Cancer Control and Population Sciences</institution>
<institution>National Cancer Institute</institution>
<addr-line>Bethesda, MD</addr-line>
<country>United States</country>
</aff>
<aff id="aff4"><sup>4</sup>
<institution>DeBartolo Family Personalized Medicine Institute at the Moffitt Cancer Center</institution>
<institution>Moffitt Cancer Center</institution>
<addr-line>Tampa, FL</addr-line>
<country>United States</country>
</aff>
<author-notes><corresp>Corresponding Author: Abdul R Shaikh <email>shaikh@us.pwc.com</email>
</corresp>
</author-notes>
<pub-date pub-type="collection"><month>4</month>
<year>2014</year>
</pub-date>
<pub-date pub-type="epub"><day>07</day>
<month>4</month>
<year>2014</year>
</pub-date>
<volume>16</volume>
<issue>4</issue>
<elocation-id>e101</elocation-id>
<history><date date-type="received"><day>15</day>
<month>12</month>
<year>2012</year>
</date>
<date date-type="rev-request"><day>27</day>
<month>3</month>
<year>2013</year>
</date>
<date date-type="rev-recd"><day>10</day>
<month>5</month>
<year>2013</year>
</date>
<date date-type="accepted"><day>03</day>
<month>3</month>
<year>2014</year>
</date>
</history>
<permissions><copyright-statement>©Abdul R Shaikh, Atul J Butte, Sheri D Schully, William S Dalton, Muin J Khoury, Bradford W Hesse. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 07.04.2014. </copyright-statement>
<copyright-year>2014</copyright-year>
<license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/2.0/"><license-p><pmc-comment>CREATIVE COMMONS</pmc-comment>
This is an open-access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/2.0/">http://creativecommons.org/licenses/by/2.0/</ext-link>
), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on <ext-link ext-link-type="uri" xlink:href="http://www.jmir.org/,">http://www.jmir.org/,</ext-link>
as well as this copyright and license information must be included.</license-p>
</license>
</permissions>
<self-uri xlink:type="simple" xlink:href="http://www.jmir.org/2014/4/e101/"></self-uri>
<abstract><p>Biomedicine is undergoing a revolution driven by high throughput and connective computing that is transforming medical research and practice. Using oncology as an example, the speed and capacity of genomic sequencing technologies is advancing the utility of individual genetic profiles for anticipating risk and targeting therapeutics. The goal is to enable an era of “P4” medicine that will become increasingly more predictive, personalized, preemptive, and participative over time. This vision hinges on leveraging potentially innovative and disruptive technologies in medicine to accelerate discovery and to reorient clinical practice for patient-centered care. Based on a panel discussion at the Medicine 2.0 conference in Boston with representatives from the National Cancer Institute, Moffitt Cancer Center, and Stanford University School of Medicine, this paper explores how emerging sociotechnical frameworks, informatics platforms, and health-related policy can be used to encourage data liquidity and innovation. This builds on the Institute of Medicine’s vision for a “rapid learning health care system” to enable an open source, population-based approach to cancer prevention and control.</p>
</abstract>
<kwd-group><kwd>biomedical research</kwd>
<kwd>crowdsourcing</kwd>
<kwd>health information technology</kwd>
<kwd>innovation</kwd>
<kwd>precision medicine</kwd>
</kwd-group>
</article-meta>
</front>
</pmc>
</record>
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