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Transferable Trustworthy Radiotherapy with Artificial Intelligence

Objective

Cancer is the leading cause of death in Europe and the second worldwide. Over 50% of patients are treated with Radiotherapy (RT) and it accounts for 40% of cures, yet recurrence and toxicities remain significant challenges. Despite major advances in imaging, planning and delivery, RT still largely follows a “one-dose-fits-all” approach, leading to variable outcomes, toxicities and limited adaptability to patient-specific biology. Europe is currently undergoing a digital transformation driven by AI, advanced imaging and the European Health Data Space, but current AI solutions in RT remain fragmented, poorly generalizable and insufficiently explainable, preventing their safe deployment in clinical practice.
TTRAIL aims at improving the safety, precision and personalization of radiotherapy (RT) by training 15 Doctoral Candidates as the first generation of Translational AI Radiotherapy Scientists, capable of uniting AI innovation with clinical radiotherapy, medical physics, regulatory science and digital-health translation. Their training will span multiscale data integration, uncertainty quantification, explainable and causal outcome modelling, digital twins and real-time adaptive dose delivery, aligned with the EU AI Act.
The consortium unites top European universities, engineering schools, cancer centers and major industrial partners, providing access to cutting-edge RT platforms, large multicentre datasets and expertise across AI, imaging, oncology, physics and regulatory compliance. This intersectoral ecosystem ensures robust scientific training, clinical immersion, industrial exposure and strong open-science practices.
By delivering a fully integrated, trust-by-design framework for AI-enabled Adaptive Radiotherapy, TTRAIL will produce highly skilled researchers able to lead the future of personalised, safe and explainable cancer treatment in Europe.

Fields of science (EuroSciVoc)

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Keywords

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Programme(s)

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Topic(s)

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Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

HORIZON-TMA-MSCA-DN - HORIZON TMA MSCA Doctoral Networks

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Call for proposal

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(opens in new window) HORIZON-MSCA-2025-DN-01

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Coordinator

UNIVERSITE DE RENNES
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 629 338,32
Address
263 AVENUE DU GENERAL LECLERC
35042 Rennes
France

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Region
Bretagne Bretagne Ille-et-Vilaine
Activity type
Higher or Secondary Education Establishments
Links
Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

No data

Participants (10)

Partners (13)

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