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Virtual Human Twin (VHT) Models for Cancer Research

European Commission

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.

AI Based Application Success Predictor

1️⃣ Strong, Mission-Aligned Impact (Most Important Across EC Calls)

The EC is impact-driven: proposals must show how the project will:

Solve a major European or global societal challenge

Deliver measurable, lasting benefits for EU citizens

Produce outputs that can be used by policymakers, industry, or society

Align with Horizon Europe missions, priorities, and strategic agendas

Predictor: Clear, quantifiable, EU-level impact → strongest scoring factor.

2️⃣ Clear, Ambitious, but Achievable Objectives

Successful proposals show:

2–4 well-defined objectives linked to the Work Programme call text

Clearly articulated research questions or innovation goals

Logical, realistic expected outcomes and deliverables

Feasible scientific and technical approaches

Predictor: Balanced ambition + feasibility.

3️⃣ Excellent, Cutting-Edge Science or Innovation

For RIA/IA/CSA or ERC-level grants, reviewers expect:

High novelty and innovation

Strong grounding in current state-of-the-art

Clear advancement beyond existing approaches

Solid theoretical or experimental foundations

Robust methodological design

Predictor: Scientific excellence is essential for competitive scoring.

4️⃣ Strong Consortium with Complementary Expertise

EC proposals are consortium-driven (except ERC/EIC Accelerator).

High-scoring consortia:

Cover all needed competencies (science, industry, policy, ethics, dissemination)

Include SMEs, industry partners, NGOs, and public bodies when relevant

Are geographically diverse across EU Member States and Associated Countries

Demonstrate strong leadership and communication structures

Predictor: Well-constructed consortium with clear roles.

5️⃣ Clear Pathway From Outputs → Outcomes → Impact

Evaluators look for a credible trajectory showing:

How research leads to specific outputs (data, tools, prototypes)

How outputs lead to uptake or use

How use produces societal, economic, scientific, or policy impact

Strong Key Performance Indicators (KPIs) and impact metrics

Predictor: Clearly mapped impact pathway.

6️⃣ Strong Implementation Plan (Work Packages, Deliverables, Gantt Chart)

Winning proposals have:

Well-designed Work Packages (WPs) with clear scope and responsibilities

Interdependencies identified and risk-mitigation strategies

Detailed milestones and deliverables

Feasible budget aligned with tasks

Strong project management plan

Predictor: High implementation quality boosts the “Excellence” and “Implementation” scores.

7️⃣ Policy Relevance and Contribution to EU Strategies

Especially critical for health, climate, digital, and social calls.

Proposals score higher when they link to:

EU Cancer Mission

EU Green Deal

Digital Europe strategy

EU Biodiversity Strategy

EU Health Union & One Health

Open Science & FAIR data mandates

Predictor: Clear alignment with EU policies.

8️⃣ Strong Stakeholder & Citizen Engagement (Especially in Social & Health Missions)

EC values inclusivity:

Patient groups

Civil society organizations

Public sector bodies

Regulatory agencies

Citizen science components

Stakeholder letters of intent or commitment strengthen credibility.

Predictor: Engagement adds impact and relevance.

9️⃣ Robust Data Management, Open Science, and Ethics

Mandatory components include:

FAIR Data Management Plan

Open access publications

Ethics self-assessment

GDPR compliance

Data security, governance, and ethical approvals

Animal-use reduction and justification (if applicable)

Predictor: Clear compliance with ethical and data obligations.

10️⃣ Well-Justified Budget and Resource Allocation

Budget must be:

Proportional to tasks

Transparent and reasonable

Efficiently distributed among partners

Free from padding or unjustified costs

Predictor: Realistic budgets improve Implementation scores.

🚫 COMMON PITFALLS THAT LEAD TO EC GRANT REJECTION

Pitfall	Why It Fails
Weak connection to Work Programme text	Immediate score reduction
Vague or generic impact statements	Poor Impact score
Overly ambitious, unrealistic scope	Feasibility concerns
Poorly structured consortium	Low Implementation score
No policy relevance	Weak strategic alignment
Lack of concrete KPIs or outcomes	Impact unclear
Weak data or ethics plan	Eligibility/score penalties
No exploitation or dissemination plan	Insufficient impact credibility
Budget misalignment	Reviewer distrust

Specialties

Cancer

Public Health

Eligibility Requirements

General conditions

1. Admissibility Conditions: Proposal page limit and layout

described in Annex A and Annex E of the Horizon Europe Work Programme General Annexes.

Proposal page limits and layout: described in Part B of the Application Form available in the Submission System.

2. Eligible Countries

described in Annex B of the Work Programme General Annexes.

A number of non-EU/non-Associated Countries that are not automatically eligible for funding have made specific provisions for making funding available for their participants in Horizon Europe projects.

Sponsor Details

Sponsor Institute/Organizations: European Commission

Sponsor Type: Corporate/Non-Profit

Address: Berlaymont Building, Rue de la Loi 200, 1049 Brussels

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