Towards standardization guidelines for in silico approaches in personalized medicine
Research output: Contribution to journal › Journal article › Research › peer-review
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Towards standardization guidelines for in silico approaches in personalized medicine. / Brunak, Søren; Bjerre, Catherine Collin; Ó Cathaoir, Katharina; Golebiewski, Martin; Kirschner, Mark; Kockum, Ingrid; Moser, Heike; Waltemath, Dagmar.
In: Journal of integrative bioinformatics, Vol. 17, No. 2-3, 2020.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - Towards standardization guidelines for in silico approaches in personalized medicine
AU - Brunak, Søren
AU - Bjerre, Catherine Collin
AU - Ó Cathaoir, Katharina
AU - Golebiewski, Martin
AU - Kirschner, Mark
AU - Kockum, Ingrid
AU - Moser, Heike
AU - Waltemath, Dagmar
PY - 2020
Y1 - 2020
N2 - 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 ofbroadly 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 datathrough 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 modelstandards and reflected on possibilities as well as challenges for cross-domain data integration to facilitate in silico modelling approaches for personalized medicine.
AB - 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 ofbroadly 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 datathrough 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 modelstandards and reflected on possibilities as well as challenges for cross-domain data integration to facilitate in silico modelling approaches for personalized medicine.
U2 - 10.1515/jib-2020-0006
DO - 10.1515/jib-2020-0006
M3 - Journal article
C2 - 32827396
VL - 17
JO - Journal of integrative bioinformatics
JF - Journal of integrative bioinformatics
SN - 1613-4516
IS - 2-3
ER -
ID: 248111074