A European standardization framework for data integration and data-driven in silico models for personalized medicine

Objective

The capacity to generate data in Life Sciences and health research with modern omics and imaging technologies has increased many orders of magnitude in the last decade. In combination with patient/personal derived data such as electronic health records, patient registries and -databases, as well as life style information this Big Data holds an immense potential for clinical applications, especially for in silico personalized medicine approaches. However, and despite the ever progressing technological advances in producing data, the exploitation of Big Data information to generate new knowledge for medical benefits, while guaranteeing data privacy and security, is lacking behind its full potential. A reason for this obstacle is the inherent heterogeneity of Big Data and the lack of broadly accepted standards that allow interoperable integration of heterogeneous health data to perform analysis and interpretation for predictive in silico modelling approaches in health research such as personalized medicine. Further obstacles are legal issues surrounding the use of personal data. To overcome these obstacles, we will establish a pan-European Expert forum with two main objectives: (i) to assess and evaluate national standardization strategies for interoperable health data integration (such as omics-, disease-focused-, clinical-/treatment- or healthcare- and socioeconomic-/lifestyle-data) as well as data-driven in silico modelling approaches and (ii) to harmonize and develop universal (cross-border) standards as well as recommendations for in silico methodologies applied in personalized medicine approaches. This pan-European Expert Forum —the EU-STANDS4PM consortium— has the overarching aim to bundle transnational standardization guidelines for in silico methodologies in transnational and clinical research to unfold the potential of personalized medicine.

Field of science

• /natural sciences/computer and information sciences/databases
• /natural sciences/computer and information sciences/data science/big data

Programme(s)

• H2020-EU.3.1.6. - Health care provision and integrated care

Topic(s)

• SC1-HCO-02-2018 - Data integration and data-driven in-silico models for enabling personalised medicine - a European standardization framework

Call for proposal

H2020-SC1-2018-Single-Stage-RTD
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Funding Scheme

Coordinator

Participants (15)