Summary
According to the 2014 European Society of Cardiology Guidelines, cardiomyopathies are defined as structural and functional abnormalities of the ventricular myocardium that are unexplained by flow limiting coronary artery disease or abnormal loading conditions. There are four major classifications of cardiomyopathy: hypertrophic (HCM), dilated (DCM), restrictive (RCM), and arrhythmogenic right ventricular (ARVC).
Familial cardiomyopathies (FCM) are most commonly diagnosed, or progress of the disease is monitored, through in vivo imaging, with either echocardiography or, increasingly, cardiac magnetic resonance imaging (MRI). The treatment of symptoms of FCM by established therapies could only in part improve the outcome, but novel therapies need to be developed to affect the disease process and time course more fundamentally.
SILICOFCM project will develop in silico computational cloud platform which will integrate from stopped-flow molecular kinetic assays to magnetic resonance imaging of the whole heart, bioinformatics and image processing tools with state of the art computer models with the aim to reduce animal and clinical studies for a new drug development and optimized clinical therapy of FCM.
The developed system will be distributed on the cloud platforms in order to achieve efficient data storage and high-performance computing, that can offer end users results in reasonably short time. Academic technical partners IIT, UOI, UL and BSC will be responsible for developing and integration of in silico cloud computational platform with multi-scale cardiac muscle modelling which include experiments on protein mutation in vitro from UNIKENT, UNIFI and UW. Bioinformatics tools will be integrated by US company SBG. Clinical partners UNEW, ICVDV, UPMC and UHREG will do retrospective and prospective studies. SME partner R-Tech will be in charge of regulatory issues and reports and BIOIRC will do the exploitation of the project.
Familial cardiomyopathies (FCM) are most commonly diagnosed, or progress of the disease is monitored, through in vivo imaging, with either echocardiography or, increasingly, cardiac magnetic resonance imaging (MRI). The treatment of symptoms of FCM by established therapies could only in part improve the outcome, but novel therapies need to be developed to affect the disease process and time course more fundamentally.
SILICOFCM project will develop in silico computational cloud platform which will integrate from stopped-flow molecular kinetic assays to magnetic resonance imaging of the whole heart, bioinformatics and image processing tools with state of the art computer models with the aim to reduce animal and clinical studies for a new drug development and optimized clinical therapy of FCM.
The developed system will be distributed on the cloud platforms in order to achieve efficient data storage and high-performance computing, that can offer end users results in reasonably short time. Academic technical partners IIT, UOI, UL and BSC will be responsible for developing and integration of in silico cloud computational platform with multi-scale cardiac muscle modelling which include experiments on protein mutation in vitro from UNIKENT, UNIFI and UW. Bioinformatics tools will be integrated by US company SBG. Clinical partners UNEW, ICVDV, UPMC and UHREG will do retrospective and prospective studies. SME partner R-Tech will be in charge of regulatory issues and reports and BIOIRC will do the exploitation of the project.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/777204 |
| Start date: | 01-06-2018 |
| End date: | 28-02-2022 |
| Total budget - Public funding: | 5 507 441,00 Euro - 5 507 441,00 Euro |
Cordis data
Original description
According to the 2014 European Society of Cardiology Guidelines, cardiomyopathies are defined as structural and functional abnormalities of the ventricular myocardium that are unexplained by flow limiting coronary artery disease or abnormal loading conditions. There are four major classifications of cardiomyopathy: hypertrophic (HCM), dilated (DCM), restrictive (RCM), and arrhythmogenic right ventricular (ARVC).Familial cardiomyopathies (FCM) are most commonly diagnosed, or progress of the disease is monitored, through in vivo imaging, with either echocardiography or, increasingly, cardiac magnetic resonance imaging (MRI). The treatment of symptoms of FCM by established therapies could only in part improve the outcome, but novel therapies need to be developed to affect the disease process and time course more fundamentally.
SILICOFCM project will develop in silico computational cloud platform which will integrate from stopped-flow molecular kinetic assays to magnetic resonance imaging of the whole heart, bioinformatics and image processing tools with state of the art computer models with the aim to reduce animal and clinical studies for a new drug development and optimized clinical therapy of FCM.
The developed system will be distributed on the cloud platforms in order to achieve efficient data storage and high-performance computing, that can offer end users results in reasonably short time. Academic technical partners IIT, UOI, UL and BSC will be responsible for developing and integration of in silico cloud computational platform with multi-scale cardiac muscle modelling which include experiments on protein mutation in vitro from UNIKENT, UNIFI and UW. Bioinformatics tools will be integrated by US company SBG. Clinical partners UNEW, ICVDV, UPMC and UHREG will do retrospective and prospective studies. SME partner R-Tech will be in charge of regulatory issues and reports and BIOIRC will do the exploitation of the project.
Status
CLOSEDCall topic
SC1-PM-16-2017Update Date
26-10-2022
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Organisations
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| ISTRAZIVACKO RAZVOJNI CENTAR ZA BIOINZENJERING BIOIRC DOO (Coördinator)
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| BARCELONA SUPERCOMPUTING CENTER - CENTRO NACIONAL DE SUPERCOMPUTACION (BSC)
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| FACULTY OF MEDICINE, UNIVERSITY OF BELGRADE
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| ILLINOIS INSTITUTE OF TECHNOLOGY
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| INSTITUT ZA KARDIOVASKULARNE BOLESTI VOJVODINE
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| KLINIKUM DER UNIVERSITAET REGENSBURG
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| PANEPISTIMIO IOANNINON
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| SEVEN BRIDGES GENOMICS BIYOTEKNOLOJI ANONIM SIRKETI
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| SEVEN BRIDGES GENOMICS D.O.O. BEOGRAD
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| SEVEN BRIDGES GENOMICS INC
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| SEVEN BRIDGES GENOMICS UK LTD
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| SORBONNE UNIVERSITE (SU)
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| STEINBEIS EU-VRI GMBH
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| UNIVERSITA DEGLI STUDI DI FIRENZE - University of Florence
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| UNIVERSITY OF KENT