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Project cooperationUpdated on 23 October 2026

Key Expertise and Contribution Areas

EU project manager at INOC - Istituto Nazionale Oncologico Candiolo

Turin, Italy

About

(HORIZON-MISS-2027-02-CANCER-04)

INOC can support:

Patient-centred cancer care research Real-world evidence generation Patient-reported outcomes and quality-of-life studies Evaluation of healthcare pathways Equity and access analyses Assessment of value-based cancer care models Stakeholder engagement including patients and healthcare providers Virtual Human Twins and AI-Based Clinical Decision Support

(HORIZON-HLTH-2027-03-TOOL-04)

INOC is particularly interested in collaborations involving:

Multi-modal oncology datasets Clinical implementation of AI tools Validation of predictive models Digital twins for oncology screening, prevention and diagnosis AI-supported clinical decision-making Federated learning and trusted health data environments AGI and Next-Generation AI for Healthcare

(HORIZON-HLTH-2027-03-TOOL-08)

INOC seeks partnerships in: (HORIZON-MISS-2027-02-CANCER-04)

INOC can support:

Patient-centred cancer care research Real-world evidence generation Patient-reported outcomes and quality-of-life studies Evaluation of healthcare pathways Equity and access analyses Assessment of value-based cancer care models Stakeholder engagement including patients and healthcare providers Virtual Human Twins and AI-Based Clinical Decision Support

(HORIZON-HLTH-2027-03-TOOL-04)

INOC is particularly interested in collaborations involving:

Multi-modal oncology datasets Clinical implementation of AI tools Validation of predictive models Digital twins for oncology screening, prevention and diagnosis AI-supported clinical decision-making Federated learning and trusted health data environments AGI and Next-Generation AI for Healthcare

(HORIZON-HLTH-2027-03-TOOL-08)

INOC seeks partnerships in:

Advanced AI and foundation models for oncology Clinical reasoning systems Multi-agent healthcare AI environments Responsible and trustworthy AI Explainable AI in clinical settings Validation of AI solutions in real-world cancer care

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