The proposed topic will contribute to the EU Cancer Mission objectives by improving the accuracy of dynamic and multiscale VHTs to better understand cancer onset, predict progression and develop personalized treatments. Of particular interest for this topic are cancers with limited treatment options or unclear biological mechanisms, refractory cancers, rare cancers, early-onset cancers, cancer types with low five-year survival rates, or paediatric and adolescent cancers.

Applicants should take advantage of technological advances in AI tools which open new opportunities to collect, combine and analyse large datasets of diverse types, including multi-omics patient data, tumour molecular profiles, immune profiles, medical images and real word data. Age, sex and gender differences should be duly considered. When relevant, proposals should build on current approaches, standards, data repositories and use modelling assets including but not limited to those provided by the future Advanced VHT Platform, the European Open Science Cloud, the European 1M+ Genomes and the European Cancer Imaging initiatives.

The applicants should address all of the following activities:

• To develop innovative, dynamic multiscale VHTs for advancing the mechanistic knowledge and understanding of cancer onset and progression and develop or improve innovative personalised treatments. VHTs should integrate AI tools for the analysis of large volumes of FAIR (Findable, Accessible, Interoperable, Reusable) multimodal data, increasing their predictive capability and, when appropriate, utilise IT solutions for model visualisation via Augmented Reality/Virtual Reality.
• To update and validate VHTs with longitudinal newly collected or existing FAIR patient data and generate evidence that VHT models can deliver clinically meaningful observations to improve treatment of the studied cancer type, demonstrating VHT accessibility and usability for clinical uptake. The use of data and services provided by ESFRI research infrastructures in the life science domain should be considered when appropriate.
• To enrich and make available data and model assets in the UNCAN.eu research platform and in the Advanced VHT Platform following the principles of open science. Newly collected patient datasets must be described with metadata records in the EU dataset catalogue of the European Health Data Space.
• Collaboration among different scientific disciplines, including healthcare professionals and patients throughout all stages of VHTs development is envisaged.

Successful proposals will be asked to join the ‘Understanding’ project cluster of the EU Cancer Mission and should include a budget for networking, attendance at meetings and joint activities. The Commission will facilitate coordination of this activity. Collaboration is encouraged also with Horizon Europe projects supporting the VHT initiative, as appropriate.

Applicants envisaging to include clinical studies should provide details in the dedicated annex using the template provided in the submission system.