Objective
We have recently observed an unexpected and profoundly promising synergy: multi-modal out-of-distribution detection methods, originally developed for normative modelling in the ERC MIA-NORMAL project, appear to endow AI agents with remarkable autonomy in real-world scientific reasoning. By explicitly encoding uncertainty and recognising unfamiliar inputs, these agents become capable of detecting anomalies, and they begin to act independently: curating data, identifying patterns, and proposing hypotheses in complex clinical domains. This breakthrough reframes the role of AI in medicine. No longer confined to fixed-task classification or retrospective association, agentic AI systems can now act as autonomous collaborators in medical discovery. We validated this concept in cardiovascular
imaging, where agents independently conducted phenome-wide association studies, rediscovered known correlations, and surfaced novel phenotype-disease links with transparent, explainable logic.
With ORACLE, we aim to extend this paradigm to oncology, focusing on pancreatic cancer, a devastating disease with limited early detection and poor outcomes. Agents will begin with large-scale, multimodal clinical data: radiology, pathology, molecular reports, and labs, and autonomously curate and structure it into patient trajectories. Once organised, agents will explore the data landscape:
clustering phenotypes, linking imaging to molecular patterns, and testing hypotheses across cohorts. When normative data is available, they compare against population-wide baselines; when it is not, agents can use our generative methods to impute missing values and identify structure.
Running entirely on real clinical data within GDPR-compliant infrastructure, ORACLE will demonstrate that autonomous AI agents can produce publishable, clinically relevant insights. This PoC may not only advance cancer research but reshape how biomedical discovery is done: transforming it into an automated, data-driven process.
Fields of science (EuroSciVoc)
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Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.1 - European Research Council (ERC)
MAIN PROGRAMME
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
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.
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-ERC-POC - HORIZON ERC Proof of Concept Grants
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2026-POC
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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.
91058 Erlangen
Germany
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.