Objective
Improving healthcare systems mandates a shift towards personalised and preventive management of disease. Specifically, the management of cardiovascular diseases has a huge impact on European society in terms of mortality, morbidity and healthcare costs, being responsible for 1.9 million deaths in the EU annually (42% of all deaths) with a total cost of €169 billion.
Advances in computational and simulation technologies now provide us with unparalleled capacity to analyse clinical data in-silico, rendering the vision of an early detection of disease through model-based diagnostic biomarkers, and the design of personalised therapies through predictive models. In-silico methodologies enable the optimization of clinical protocols, from data acquisition to device parameters and intervention choices. In-silico tools also enable the reduction of animal use in the development of novel cardiac therapies and drugs.
PIC is the European ITN that will train the cohort of 15 of the future innovation leaders able to articulate and materialise the vision of a Personalised In-silico Cardiology (PIC). It will address specific challenges originated by cultural and structural barriers between sectors and disciplines, articulating a fluent dialogue and work between clinicians and engineers. Fellows will be exposed to the generation of novel academic ideas, the design of practical solutions that meet actual clinical needs, the translation into industrial products, and the compliance with safety and regulation requirements.
This will be achieved by pooling the expertise of leading experts from 4 academic, 3 industrial and 3 clinical beneficiaries. A highly inter-disciplinary program will be delivered in 4 research work packages, with companies leading two of them. New talent and innovation will be produced through the training in the disciplines of computational cardiac modelling, medical imaging & sensing, and clinical devices & instrumentation.
Fields of science
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- medical and health sciencesclinical medicinecardiologycardiovascular diseasescardiac arrhythmia
- natural sciencescomputer and information sciencesdata sciencedata mining
- natural sciencesphysical sciencesclassical mechanicsfluid mechanicsfluid dynamics
- natural sciencesmathematicsapplied mathematicsstatistics and probability
- engineering and technologymedical engineeringdiagnostic imaging
Programme(s)
Coordinator
WC2R 2LS London
United Kingdom
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Participants (9)
0450 Oslo
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9052 Gent
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
OX1 2JD Oxford
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6200 MD Maastricht
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50009 Zaragoza
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33000 Bordeaux
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08036 Barcelona
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3191 Horten
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6229GW Maastricht
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Partners (9)
Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
Oxford
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
Silver Spring
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
0458 Oslo
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
Armonk
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
Barcelona
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
2340 Beerse
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
Oxford
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
Zurich
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
Leuven
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