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EU-Förderung (10,3 Mio. €): PRedictive In-silico Multiscale Analytics zur Unterstützung von krebspersonalisierter Diagnose und Prognose, gestärkt durch bildgebende Biomarker Hor01.12.2018 EU-Rahmenprogramm für Forschung und Innovation "Horizont"
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PRedictive In-silico Multiscale Analytics zur Unterstützung von krebspersonalisierter Diagnose und Prognose, gestärkt durch bildgebende Biomarker
PRIMAGE proposes a cloud-based platform to support decision making in the clinical management of malignant solid tumours, offering predictive tools to assist diagnosis, prognosis, therapies choice and treatment follow up, based on the use of novel imaging biomarkers, in-silico tumour growth simulation, advanced visualisation of predictions with weighted confidence scores and machine-learning based translation of this knowledge into predictors for the most relevant, disease-specific, Clinical End Points. PRIMAGE implements a hybrid cloud model, comprising the of use of open public cloud (based on EOSC services) and private clouds, enabling use by the scientific community (facilitating reuse of de-identified clinical curated data in Open Science) and also suitable for future commercial exploitation. The proposed data infrastructures, imaging biomarkers and models for in-silico medicine research will be validated in the application context of two paediatric cancers, Neuroblastoma (NB, the most frequent solid cancer of early childhood) and the Diffuse Intrinsic Pontine Glioma (DIPG, the leading cause of brain tumour-related death in children). These two paediatric cancers are relevant validation cases given their representativeness of cancer disease, and their high societal impact, as they affect the most vulnerable and loved family members. The European Society for Paediatric Oncology, two Imaging Biobanks and three of the most prominent European Paediatric oncology units are partners in this project, making retrospective clinical data (imaging, clinical, molecular and genetics) registries accessible to PRIMAGE, for training of machine learning algorithms and testing of the in-silico tools´ performance. Solutions to streamline and secure the data pseudonymisation, extraction, structuring, quality control and storage processes, will be implemented and validated also for use on prospective data, contributing European shared data infrastructures.
Geförderte Unternehmen:
| Firmenname | Förderungssumme |
| Akademia Gorniczo-Hutnicza im. Stanislawa Staszica w Krakowie | 538.566 € |
| Alma Mater Studiorum - Universita Di Bologna | 192.314 € |
| Ansys France SAS | 810.874 € |
| BC Platforms | 384.806 € |
| Chemotargets SL | 661.326 € |
| Fundacion para La Investigacion del Hospital Universitario La Fe de La Comunidad Valenciana | 1.243.342 € |
| KLINIKUM DER UNIVERSITAET ZU KOELN | 751.375 € |
| Matical Innovation SL | 380.756 € |
| Quibim SL | 919.064 € |
| Siop Europe | 323.364 € |
| ST. Anna Kinderkrebsforschung GmbH | 842.512 € |
| ST Anna Kinderkrebsforschung Verein | 0,00 € |
| The University of Sheffield | 616.680 € |
| Universidad de Zaragoza | 796.184 € |
| Universita Di Pisa | 637.564 € |
| UNIVERSITAT KONSTANZ | 756.066 € |
| Universitat Politecnica de Valencia | 457.126 € |
Quelle: https://cordis.europa.eu/project/id/826494
Diese Bekanntmachung wurde von Englisch nach Deutsch übersetzt. Die Bekanntmachung bezieht sich auf einen vergangenen Zeitpunkt, und spiegelt nicht notwendigerweise den heutigen Stand wider.
