Virtual Human Twin (VHT) Models for Cancer Research

Expected Outcome

Proposals under this topic should aim to deliver results that are directed and tailored towards and contribute to all of the following expected outcomes:

• Researchers of different disciplines use advanced multiscale Virtual Human Twins (VHTs) to expand the knowledge and understanding of cancer onset and progression
• Healthcare professionals and researchers have access to advanced VHT-based solutions that model cancer onset and progression over time, contributing to improve personalised treatments
• Researchers, healthcare professionals, innovators and citizens have access to cancer VHTs through the UNCAN.eu and the advanced Virtual Human Twin platforms

Scope

Virtual human twins (VHTs) are digital representations and in-silico models of an individual’s health and disease at different levels of the human anatomy (e.g. cells, tissues, organs or organ systems) for the prevention, prediction, screening, diagnosis and treatment of a disease, as well as the selection and personalisation of intervention options[1].

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[2].

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[3], the European Open Science Cloud[4], the European 1M+ Genomes[5] and the European Cancer Imaging initiatives[6].

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[7] 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[8].

Successful proposals will be asked to join the 'Understanding' project cluster of the EU Cancer Mission[9] and should include a budget for networking, attendance at meetings and joint activities[10]. The Commission will facilitate coordination of this activity. Collaboration is encouraged also with Horizon Europe projects supporting the VHT initiative[11], as appropriate.

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

[1] See the ‘European Virtual Human Twin’ Coordination and Support Action, EDITH, funded under the DIGITAL programme https://www.edith-csa.eu/

[2] Age at first diagnosis 0-19 years

[3] https://digital-strategy.ec.europa.eu/en/funding/platform-advanced-virtual-human-twin-vht-models

[4] https://research-and-innovation.ec.europa.eu/strategy/strategy-research-and-innovation/our-digital-future/open-science/european-open-science-cloud-eosc_en

[5] European '1+ Million Genomes' Initiative | Shaping Europe’s digital future

[6] European Cancer Imaging Initiative | Shaping Europe’s digital future

[7] https://lifescience-ri.eu/home.html

[8] Proposals should include an appropriate mix of stakeholders from various disciplines and sectors, including but not limited to medical doctors, patient representatives, health-IT experts, researchers, AI-experts, solution providers, academia and research institutes, EU research infrastructures, and SMEs

[9] In order to address the objectives of the Cancer Mission, participants will collaborate in project clusters to leverage EU-funding, increase networking across sectors and disciplines, and establish a portfolio of Cancer Mission R&I and policy actions

[10] Examples of those activities are organising joint workshops, establishing best practices, joint communication or citizen engagement activities with projects funded under other clusters and pillars of Horizon Europe, or other EU programmes, as appropriate. Proposals are not required to include details of these activities, as they will be defined during the grant agreement preparation and during the life of the project

[11] Including the projects funded under call HORIZON-HLTH-2023-TOOL-05-03, https://hadea.ec.europa.eu/calls-proposals/horizon-europe-health-calls-2023-destination-5-unlocking-full-potential-new-tools-technologies-and_en