Virtual Human Twins (VHTs) for integrated clinical decision support in prevention and diagnosis

Expected Outcome:

This topic aims at supporting activities that are enabling or contributing to one or several expected impacts of destination “Developing and using new tools, technologies and digital solutions for a healthy society”. To that end, proposals under this topic should aim to deliver results that are directed at, tailored towards and contributing to all the following expected outcomes:

• Healthcare professionals have access to multi-scale [1] , multi-organ models of individual patients that aim to improve prevention and diagnosis in high disease burden areas.
• Health professionals benefit from enhanced knowledge of complex diseases and co-morbidities by recourse to multi-scale, multi-organ models.
• Patients with diverse characteristics (e.g. of any sex, age group, racial or ethnic origin [2] ) benefit from improved, integrated and personalised prevention and diagnostics tools.
• Health professionals and patients benefit from the use of “Virtual Human Twin” (VHT) models which enable integration of other preventive and diagnostic tools and modalities.

Scope:

VHTs are digital representations and in-silico models of an individual’s health and disease state at different levels of anatomy. Multi-scale, multi-organ VHT solutions have a potential for tailored prevention and diagnosis, particularly in areas of high disease burden, and can significantly benefit citizens' health and the efficiency of EU health systems. Proposals should take into account the work of projects funded under topic HORIZON-HLTH-2023-TOOL-05-03: “Integrated, multi-scale computational models of patient patho-physiology (‘virtual twins’) for personalised disease management”, which had a predominant focus on disease management, and focus on high-potential multi-disciplinary approaches at greater complexity (multiscale, multiorgan, longitudinal), strengthening their deployment in health and care, including the integration into care pathways and links with other decision support tools. The proposals should address all the following activities:

• Select clinical use cases to deliver multi-disciplinary, high impact solutions requiring multi-organ, multi-scale approaches to modelling complex pathophysiology over time, as a basis from where prevention and diagnosis of diseases with high morbidity and mortality could be enhanced. Proposals can put forward use cases in any areas of high disease burden; examples include co-morbidities, chronic cardiovascular conditions, infection and (auto)immunity, inflammation and cancer, diabetes and related conditions, rare diseases, degenerative diseases (including their interaction with mental health conditions), the exposome and its impact on human health and disease.
• Building on current approaches, standards, data repositories (e.g. biobanks, environmental data, others) and modelling assets (e.g. those of the EDITH CSA [3] and the Platform for Advanced VHT Models [4] ), and new data if relevant, design, develop, extend and validate multi-organ, multi-scale, dynamic computational models that accurately simulate a person’s health and disease states, as necessary.
• Evaluate, select, extend and validate diverse modelling methodologies, resulting in integrated, advanced, interoperable, patient-specific VHT models that can integrate diverse data sources and methodologies, addressing the chosen clinical use case requirements. Methodologies may include and are not limited to biophysics-based modelling, artificial intelligence (AI) that should be interpretable or allow explainability of outcomes, generative AI and in-silico modelling, agent-based and network physiology approaches. Evaluation, selection and extension of these should be documented during the design phase. Availability and integration of the multi-modal data should be documented, and the ethical and sex dimensions be investigated.
• Demonstrate integration of these models with other advanced preventive and diagnostic modalities, tools and techniques enabling integration across pathways.
• Generate evidence, including clinical validation, that the solutions deliver clinically meaningful decision support, addressing use case requirements. Document lessons-learned for broader application. Gather evidence via health economic and/or feasibility studies in real-world healthcare settings confirming cost-effectiveness vis-à-vis current practice (e.g. cost-effectiveness analysis). Produce an exploitation plan on regulatory compliance [5] and intellectual property.

Proposals should be multidisciplinary; solution design and development should be end-user-focused and draw on user and non-user input. Best practice in VHT software development including responsible AI development should be followed (e.g. risk assessment and management, requirements definition process).

Participation of small and medium-sized enterprises (SMEs) [6] is encouraged

Proposals should contribute to the objectives of the European VHT Initiative [7] and to the Platform for Advanced VHT Models, with project assets made available on the Platform and interoperable with its technical specifications [8] ; relevant consortia members should join its User Community. Budget should be reserved for these activities. Projects are expected to collaborate with other EU-funded projects on VHTs [9] and align with relevant EU initiatives funded under Horizon Europe, the Digital Europe Programme [10] and the EU4Health Programme (2021-2027) [11] , e.g. European Cancer Imaging Initiative [12] , 1+Million Genomes Initiative [13] , Intensive Care Unit Data Space [14] , co-funded European Partnership for Personalised Medicine [15] , and projects on advancing AI in health where relevant. This topic requires the effective contribution of social sciences and humanities (SSH) disciplines and the inclusion of relevant SSH expertise, in order to produce meaningful and significant effects enhancing the societal impact of the related research activities. Applicants should provide details of their clinical studies [16] in the dedicated annex using the template provided in the submission system. As proposals under this topic are expected to include clinical studies, the use of the template is strongly encouraged. [1] In the context of this topic, multi-scale refers to modelling at different levels of human anatomy, e.g. at (sub-)cellular, tissue, organ or organ system level. [2] The use of the term ‘racial or ethnic origin’ does not imply an acceptance of theories that attempt to determine the existence of separate human races. [3] See the “European Virtual Human Twin” Coordination and Support Action EDITH, funded under the Digital Europe Programme: https://www.edith-csa.eu [4] Funded under the Digital Europe Programme, procedure identifier EC-CNECT/LUX/2024/OP/0014: https://ec.europa.eu/info/funding-tenders/opportunities/portal/screen/opportunities/tender-details/16cc3c6a-844a-42d4-9746-dcc7444b8001-CN [5] For example with Regulation (EU) 2017/745 on medical devices: http://data.europa.eu/eli/reg/2017/745/oj , Regulation (EU) 2017/746 on in vitro diagnostic medical devices: http://data.europa.eu/eli/reg/2017/746/2025-01-10 , Regulation (EU) 2024/1689 laying down harmonised rules on artificial intelligence: http://data.europa.eu/eli/reg/2024/1689/oj

[6] https: //eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:32003H0361

[7] https: //digital-strategy.ec.europa.eu/en/policies/virtual-human-twins

[8] No contact with the developer of the Platform is required at proposal stage. [9] Including the projects funded under topic HORIZON-HLTH-2023-TOOL-05-03: “Integrated, multi-scale computational models of patient patho-physiology (‘virtual twins’) for personalised disease management”

[10] https: //digital-strategy.ec.europa.eu/en/activities/digital-programme

[11] https: //commission.europa.eu/funding-tenders/find-funding/eu-funding-programmes/eu4health_en

[12] https: //digital-strategy.ec.europa.eu/en/policies/cancer-imaging

[13]