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Towards standardization guidelines for in silico approaches in personalized medicine

Despite the ever-progressing technological advances in producing data in health and clinical research, the generation of new knowledge for medical benefits through advanced analytics still lags behind its full potential. Reasons for this obstacle are the inherent heterogeneity of data sources and th...

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Autores principales: Brunak, Søren, Bjerre Collin, Catherine, Eva Ó Cathaoir, Katharina, Golebiewski, Martin, Kirschner, Marc, Kockum, Ingrid, Moser, Heike, Waltemath, Dagmar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: De Gruyter 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7756614/
https://www.ncbi.nlm.nih.gov/pubmed/32827396
http://dx.doi.org/10.1515/jib-2020-0006
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author Brunak, Søren
Bjerre Collin, Catherine
Eva Ó Cathaoir, Katharina
Golebiewski, Martin
Kirschner, Marc
Kockum, Ingrid
Moser, Heike
Waltemath, Dagmar
author_facet Brunak, Søren
Bjerre Collin, Catherine
Eva Ó Cathaoir, Katharina
Golebiewski, Martin
Kirschner, Marc
Kockum, Ingrid
Moser, Heike
Waltemath, Dagmar
author_sort Brunak, Søren
collection PubMed
description Despite the ever-progressing technological advances in producing data in health and clinical research, the generation of new knowledge for medical benefits through advanced analytics still lags behind its full potential. Reasons for this obstacle are the inherent heterogeneity of data sources and the lack of broadly accepted standards. Further hurdles are associated with legal and ethical issues surrounding the use of personal/patient data across disciplines and borders. Consequently, there is a need for broadly applicable standards compliant with legal and ethical regulations that allow interpretation of heterogeneous health data through in silico methodologies to advance personalized medicine. To tackle these standardization challenges, the Horizon2020 Coordinating and Support Action EU-STANDS4PM initiated an EU-wide mapping process to evaluate strategies for data integration and data-driven in silico modelling approaches to develop standards, recommendations and guidelines for personalized medicine. A first step towards this goal is a broad stakeholder consultation process initiated by an EU-STANDS4PM workshop at the annual COMBINE meeting (COMBINE 2019 workshop report in same issue). This forum analysed the status quo of data and model standards and reflected on possibilities as well as challenges for cross-domain data integration to facilitate in silico modelling approaches for personalized medicine.
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spelling pubmed-77566142020-12-30 Towards standardization guidelines for in silico approaches in personalized medicine Brunak, Søren Bjerre Collin, Catherine Eva Ó Cathaoir, Katharina Golebiewski, Martin Kirschner, Marc Kockum, Ingrid Moser, Heike Waltemath, Dagmar J Integr Bioinform Workshop Despite the ever-progressing technological advances in producing data in health and clinical research, the generation of new knowledge for medical benefits through advanced analytics still lags behind its full potential. Reasons for this obstacle are the inherent heterogeneity of data sources and the lack of broadly accepted standards. Further hurdles are associated with legal and ethical issues surrounding the use of personal/patient data across disciplines and borders. Consequently, there is a need for broadly applicable standards compliant with legal and ethical regulations that allow interpretation of heterogeneous health data through in silico methodologies to advance personalized medicine. To tackle these standardization challenges, the Horizon2020 Coordinating and Support Action EU-STANDS4PM initiated an EU-wide mapping process to evaluate strategies for data integration and data-driven in silico modelling approaches to develop standards, recommendations and guidelines for personalized medicine. A first step towards this goal is a broad stakeholder consultation process initiated by an EU-STANDS4PM workshop at the annual COMBINE meeting (COMBINE 2019 workshop report in same issue). This forum analysed the status quo of data and model standards and reflected on possibilities as well as challenges for cross-domain data integration to facilitate in silico modelling approaches for personalized medicine. De Gruyter 2020-07-24 /pmc/articles/PMC7756614/ /pubmed/32827396 http://dx.doi.org/10.1515/jib-2020-0006 Text en © 2020 Søren Brunak et al., Published DeGruyter, Berlin/Boston http://creativecommons.org/licenses/by/4.0 This work is licensed under the Creative Commons Attribution 4.0 International License.
spellingShingle Workshop
Brunak, Søren
Bjerre Collin, Catherine
Eva Ó Cathaoir, Katharina
Golebiewski, Martin
Kirschner, Marc
Kockum, Ingrid
Moser, Heike
Waltemath, Dagmar
Towards standardization guidelines for in silico approaches in personalized medicine
title Towards standardization guidelines for in silico approaches in personalized medicine
title_full Towards standardization guidelines for in silico approaches in personalized medicine
title_fullStr Towards standardization guidelines for in silico approaches in personalized medicine
title_full_unstemmed Towards standardization guidelines for in silico approaches in personalized medicine
title_short Towards standardization guidelines for in silico approaches in personalized medicine
title_sort towards standardization guidelines for in silico approaches in personalized medicine
topic Workshop
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7756614/
https://www.ncbi.nlm.nih.gov/pubmed/32827396
http://dx.doi.org/10.1515/jib-2020-0006
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