On January 1st 2019 the Horizon2020 Coordinating and Support Action “EU-STANDS4PM - A European standardization framework for data integration and data-driven in silico models for personalised medicine” launched activities.
A European standardization framework for data integration and data-driven in silico models
for personalised medicine
EU-STANDS4PM is a Coordinating and Support Action funded under the Horizon2020 framework programme of the European Commission. Core of the project is a pan-European expert forum and network that combines extensive experience from its sixteen partners, including H2020 collaborative research projects, normative and regulatory agencies, large European infrastructures, Industry as well as ethical and legal expertise from eight European countries.
During the next three years EU-STANDS4PM will initiate an EU-wide mapping process to assess and evaluate strategies for data-driven in silico modelling approaches. A central goal is to develop harmonised transnational standards, recommendations and guidelines that allow a broad application of predictive in silico methodologies in personalised medicine across Europe.
Programme: European Commission H2020 Work Programme 2018-2020 - Health, demographic change and wellbeing
Call: Data integration and data-driven in-silico models for enabling personalised medicine - a European standardization framework (SC1-HCO-02-2018)
Project titel: Data integration and data-driven in-silico models for enabling personalised medicine - a European standardization framework (EU-STANDS4PM)
Type of Action: Coordination and support action
Budget: 2.0 Million Euro
Project duration: 3 years (01/2019 - 12/2021)
Consortium: 16 partners, 8 countries
Coordinator: Forschungszentrum JülichGmbH, Project Management Juelich
EU-STANDS4PM is an open network and seeks input from all relevant stakeholders that have an interest in advancing predictive in silico methodologies in personalised medicine through broadly applicable standards for data integration and harmonisation. Our goal is to sustain the competitiveness of the European Research Area and to ensure a leading role for the European personalised medicine community of stakeholders in the transition from current reactive medical practice to a data-driven and predictive medicine of the future.
The EU-STANDS4PM consortium has the overarching aim to bundle transnational standardization guidelines for in silico methodologies in transnational and clinical research to:
Although Big Data already drives fundamental medical/scientific applications and the associated socioeconomic potential forward, a large-scale future exploitation of Big Data in research and health care represents a major challenge.
Currently there are no widely accepted, overarching strategies or concepts to harmonise the integration of heterogeneous health/disease data and data-driven in silico approaches that interpret Big Data to enable personalised medicine.
While the technological basis for the generation of data and their storage is relatively trivial from an IT perspective, the analysis of data, however, relies on the sharing and integration of data and this relies on standards.
A wide adoption of standards, best practices and data harmonization strategies is key to ensure future benefits for in silico approaches in personalized medicine.
The development of in silico models for personalised medicine in the EU requires lawful and ethical data integration. The ultimate use of these models will also require the use of information in these automated systems in a fair and transparent way, which respects patients’ rights.Download: Legal and ethical review of in silico modelling
Webinar on “formal” standardization efforts for data in the life sciences that tries to bridge between community standards and ISO standards. Given by EU-STANDS4PM partner HITS (The Heidelberg Institute for Theoretical Studies, speaker: Martin Golebiewski).
EU-wide mapping of methodologies for integration of large-scale health data (big data) for predictive in silico modeling approaches in personalized medicine.