project . 2021 - 2026 . On going

DECIDER

Improved clinical decisions via integrating multiple data levels to overcome chemotherapy resistance in high-grade serous ovarian cancer

Open Access mandate for Publications and Research DataOpen Access mandate for ... European Commission

Funder: European CommissionProject code: 965193 Call for proposal: H2020-SC1-2020-Single-Stage-RTD
Funded under: H2020 | RIA Overall Budget: 14,999,300 EURFunder Contribution: 14,999,300 EUR
Status: On going
Start Date
01 Feb 2021
End Date
31 Jan 2026
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Summary
Publications
Research Data
Software
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Dmps

Description

The goals of this inter-disciplinary project are to 1) gain understanding of the mechanisms causing chemoresistance in high-grade serous ovarian cancer (HGSOC) patients, 2) deliver tools that enable effective and cost-efficient personalised treatment options for HGSOC patients, and 3) commercialise predictive kits & software for treatment response prediction and finding the right therapeutic regimen to the right patient. This project takes an advantage on prospectively and longitudinally collected fresh and blood specimens of HGSOC patients. Longitudinal, multi-layer data are analysed with ML and AI methods to predict patient treatment response and identify the ...

Partners

AIFORIA TECHNOLOGIES OY, VEIL.AI OY, Karolinska Institutet Innovations (Sweden), HUS, UNIMORE, HELSINGIN YLIOPISTO, TUCH, Institut Pasteur, University Hospital Heidelberg, FUNDACIO INSTITUT DE RECERCA BIOMEDICA (IRB BARCELONA), 2CUREX A/S, DCS, BSC, AB Analitica

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Link existing DMPs with this project or start a new DMP in Argos.

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