PRIMAGE

PRedictive In-silico Multiscale Analytics to support cancer personalized diaGnosis and prognosis, Empowered by imaging biomarkers

Abstract

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.

Project details

Unibo Team Leader: Marco Viceconti

Unibo involved Department/s:
Dipartimento di Ingegneria Industriale

Coordinator:
Fondacion Para La Investigacion Del Hospital Universitario La Fe De La Comunidad Valenciana (Hulafe)(Spain)

Other Participants:
Universidad De Zaragoza (Spain)
Universitat Politècnica de València (Spain)
St. Anna Kinderkrebsforschung E.V. (Austria)
Chemotargets S.L. (Spain)
Quibim Sociedad Limitada (Spain)
SIOP EUROPE ASBL-The European Society for Paediatric Oncology (Belgium)
Medexprim (France)
Universitaet Zu Koeln (Germany)
The University Of Sheffield Usfd (United Kingdom)
Ansys France Sas (France)
ALMA MATER STUDIORUM - Università di Bologna (Italy)
Matical Innovation Sl (Spain)
Università  di PISA (Italy)
Akademia Gorniczo-Hutnicza Im. Stanislawa Staszica W Krakowie (Poland)
Universität Konstanz (Germany)

Total Eu Contribution: Euro (EUR) 10.311.920,25
Project Duration in months: 53
Start Date: 01/12/2018
End Date: 30/05/2023

Cordis webpage
Project website

Good health and well-being This project contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.

UE flag This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 826494