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] https://digital-strategy.ec.europa.eu/en/policies/1-million-genomes [14] https://ec.europa.eu/info/funding-tenders/opportunities/portal/screen/opportunities/topic-details/digital-2023-cloud-ai-04-icu-data [15] https://cordis.europa.eu/project/id/101137129 , https://www.eppermed.eu [16] Please note that the definition of clinical studies (see introduction to this Work Programme part) is broad and it is recommended that you review it thoroughly before submitting your application.

Topics under this destination are directed towards the Key Strategic Orientation 2 “ The Digital Transition ” and Key Strategic Orientation 3 “ A More Resilient, Competitive, Inclusive, and Democratic Europe ” of Horizon Europe’s strategic plan 2025-2027 [1] . Research and Innovation supported under this destination should contribute to the following expected impact, set out in the strategic plan impact summary for the Health Cluster: “ Health technologies, data, new tools, and digital solutions are applied effectively thanks to their inclusive, ethically sound, secure and sustainable delivery, integration and deployment in health policies and in health and care systems. ” The Health Cluster will continue to drive the development and adoption of innovative technologies and digital solutions to improve healthcare and health systems. This will ensure that the EU remains at the forefront of breakthrough health and medical technologies and can achieve open strategic autonomy in essential medical supplies and digital innovations. In line with the Commission's Political Guidelines for 2024-2029 [2] , this destination will support research and innovation in tools and technologies strengthening the competitiveness of European health industry and reinforcing EU autonomy. This effort will contribute to the completion of the European Health Union which aims to enhance the resilience of healthcare systems, facilitate access to innovative and affordable healthcare solutions, and ensure that all citizens have access to high-quality, equitable, inclusive and sustainable healthcare. The development and use of innovative tools and technologies for biomedical research are the basis for prevention, early diagnosis, efficacious therapy and patient monitoring, essential components of efficient healthcare. These include enabling technologies, not least innovative biotechnological approaches, and emerging technologies like synthetic biology, digital tools including those based on Machine-Learning/Artificial Intelligence (ML/AI) and other data-driven approaches which will enable the development of more personalised medicine. Hence the combination of innovative tools, high-quality health data (incl. Real-World Data - RWD [3] ), digital technologies, modelling and AI tools holds great potential not only for advancing biomedical Research and Innovation but for developing health technologies that improve healthcare. However, the implementation of these tools and technologies faces specific barriers such as scalability, regulatory frameworks and public acceptance and trust. To overcome these challenges cross-sectoral cooperation among stakeholders including researchers, regulatory bodies, policymakers, industry, healthcare providers and patients, is necessary. This collaboration will facilitate the design and development of innovative health products and services, tailored to specific population groups, ultimately improving patient outcomes and reducing health inequalities. By taking a comprehensive and inclusive approach, this destination will prioritise the development of novel tools and technologies that address key considerations such as the rights of the individual, safety, effectiveness, appropriateness, accessibility, comparative value-added and fiscal sustainability while also ensuring ethical, legal and regulatory compliance. In this Work Programme part, Destination “ Developing and using new tools, technologies and digital solutions for a healthy society ” is driven mainly by three key Commission policies, the “Biotechnology and Biomanufacturing Communication” [4] the “Artificial Intelligence Strategy” [5] and the “Strategy for European Life Sciences” [6] and focuses on developing and applying innovative technologies to improve human health and healthcare systems. The topics under this destination cover efforts to develop AI based predictive biomarkers for disease prognosis and treatment response, advancing bio-printing of living cells for regenerative medicine, and integrating New Approach Methodologies (NAMs) to advance biomedical research, as well as developing virtual human twins for integrated clinical decision support. To increase the impact of EU investments under Horizon Europe, the Commission encourages cooperation between EU-funded projects to enable cross-fertilisation and other synergies. For example, this cooperation could take the form of networking, to joint activities, such as the participation in joint workshops, exchange of knowledge, development and adoption of best practices, or joint communication activities. Opportunities for such activities and potential synergies exist between projects funded under the same topic but also between other projects funded under different topics, Clusters or Pillars of Horizon Europe. Specifically, this could involve projects related to European health research infrastructures (under Pillar I of Horizon Europe), the EIC [7] strategic challenges on health (under Pillar III of Horizon Europe) or with projects on themes that cut across the Clusters of Pillar II such as with Cluster “Digital, Industry and Space” on digitalisation of the health sector or key enabling technologies. Expected Impacts : Proposals for topics under this destination should set out a credible pathway towards the development and use of new tools, technologies and digital solutions for a healthy society, and more specifically to one or several of the following impacts: Europe’s scientific and technological expertise and know-how, its capabilities for innovation in new tools, technologies and digital solutions, and its ability to take-up, scale-up and integrate innovation in healthcare is world-class. Citizens benefit from targeted and faster research resulting in safer, more sustainable, efficient, cost-effective, accessible and affordable tools, technologies and digital solutions for improved (personalised) disease prevention, diagnosis, treatment and monitoring for better patient outcome and wellbeing, in particular through increasingly shared health resources (interoperable data, infrastructure, expertise, citizen/patient driven co-creation) [8] . The EU gains high visibility and leadership in terms of health technology development, including through international cooperation. The burden of diseases in the EU and worldwide is reduced through the development and integration of innovative diagnostic and therapeutic approaches, personalised medicine approaches, digital and other people-centred solutions for healthcare. Both the productivity of health Research and Innovation, and the quality and outcome of healthcare is improved thanks to the use of health data and innovative analytical tools, such as AI supported decision-making, in a secure, ethical and inclusive manner, respecting individual integrity and underpinned with public acceptance and trust. Citizens trust and support the opportunities offered by innovative technologies for healthcare, based on expected health outcomes and potential risks involved. Legal entities established in China are not eligible to participate in both Research and Innovation Actions (RIAs) and Innovation Actions (IAs) falling under this destination. For additional information please see “Restrictions on the participation of legal entities established in China” found in the Annex B of the General Annexes of this Work Programme. The protection of European communication networks has been identified as an important security interest of the Union and its Member States. Entities that are assessed as high-risk suppliers [9] of mobile network communication equipment (and any entities they own or control) are not eligible to participate as beneficiaries, affiliated entities and associated partners to topics identified as “subject to restrictions for the protection of European communication networks”. Please refer to the Annex B of the General Annexes of this Work Programme for further details. [1] https://research-and-innovation.ec.europa.eu/funding/funding-opportunities/funding-programmes-and-open-calls/horizon-europe/strategic-plan_en [2] https://commission.europa.eu/about/commission-2024-2029_en [3] EMA definition: “Real-World Data are routinely collected data relating to patient health status or the delivery of healthcare from a variety of sources other than traditional clinical trials (e.g. claims databases, hospital data, electronic health records, registries, mhealth data, etc.)”. [4] Commission Communication on Building the future with nature: Boosting Biotechnology and Biomanufacturing in the EU; COM(2024) 137 final: https://research-and-innovation.ec.europa.eu/document/download/47554adc-dffc-411b-8cd6-b52417514cb3_en [5] Commission Communication on Artificial Intelligence for Europe; COM(2018) 237 final: https://digital-strategy.ec.europa.eu/en/policies/european-approach-artificial-intelligence ; https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=COM:2018:237:FIN [6] https://research-and-innovation.ec.europa.eu/strategy/strategy-research-and-innovation/jobs-and-economy/towards-strategy-european-life-sciences_en ; https://ec.europa.eu/commission/presscorner/detail/en/ip_25_1686 [7] https://eic.ec.europa.eu [8] Commission Communication on the digital transformation of health and care; COM(2018) 233 final [9] Entities assessed as “high-risk suppliers”, are currently set out in the second report on Member States’ progress in implementing the EU toolbox on 5G cybersecurity of 2023 (NIS Cooperation Group, Second report on Member States’ progress in implementing the EU Toolbox on 5G Cybersecurity, June 2023) and the related Communication on the implementation of the 5G cybersecurity toolbox of 2023 (Communication from the Commission: Implementation of the 5G cybersecurity Toolbox, Brussels, 15.6.2023 C(2023) 4049 final).

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