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Mechanism-Informed Multimodal Generative AI for Causal and Dynamical Modelling in Biomedical Research

Objective

AIRIS will develop the next generation of multimodal Generative AI (GenAI) models to accelerate research on predictive and personalised medicine. Building on recent advances in LLMs, causal inference and mechanistic modelling, AIRIS will integrate heterogeneous biomedical data (omics, imaging, clinical, laboratory, lifestyle, PROMs and scientific literature) into mechanism-informed generative frameworks. These models will not only generate biologically plausible synthetic data to address sparsity and bias but also embed causal and dynamical constraints across biological scales, from “virtual cells” to multi-organ models, enabling counterfactual reasoning and in-silico hypothesis testing. The project will deliver (i) robust agentic multimodal data integration pipelines; (ii) novel mechanism-anchored generative architectures with interpretability and bias-mitigation safeguards; (iii) hypothesis generation assistants for biomarker discovery, drug repurposing, and intervention design; and (iv) a scalable MLOps infrastructure ensuring reproducibility. AIRIS will be validated using already existing large-scale datasets in five high-impact use cases including Pulmonary Fibrosis, Steatotic Liver Disease, Cardiovascular Disease, Chronic Kidney Disease and Inflammatory Bowel Disease. AIRIS will demonstrate utility in modelling of disease, while also allowing cross-disease insights. A multidisciplinary consortium spanning leading universities and research centres, HPC experts, industry, and SME ensures excellence across the project dimensions. ELSI and fairness will be systematically addressed by SSH and legal experts. Outputs will be openly disseminated through benchmarks, training, and open-source releases, fostering European leadership in mechanism-informed GenAI. AIRIS will maximise scientific, clinical, and societal impact by bridging AI innovation with biomedical discovery, improving disease understanding, and supporting equitable personalised care.

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Keywords

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Programme(s)

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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.

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-RIA - HORIZON Research and Innovation Actions

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) HORIZON-HLTH-2025-01

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Coordinator

ATHINA-EREVNITIKO KENTRO KAINOTOMIAS STIS TECHNOLOGIES TIS PLIROFORIAS, TON EPIKOINONION KAI TIS GNOSIS
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.

€ 1 757 500,00
Address
ARTEMIDOS 6 KAI EPIDAVROU
151 25 MAROUSSI
Greece

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Αττική Aττική Κεντρικός Τομέας Αθηνών
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Research Organisations
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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.

€ 1 757 500,00

Participants (21)

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