Expected Outcome:

This topic aims at supporting activities that are enabling or contributing to one or several expected impacts of destination “Tackling diseases and reducing disease burden”. 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 providers, policymakers and researchers benefit from an improved knowledge base and collaboration on the key challenges and gaps on cardiovascular health research and a conceptual framework to develop a roadmap for research and innovation is established.
• Health systems gain improved and standardised evidence to better prevent, diagnose or treat cardiovascular diseases (CVDs) and associated comorbidities, based on the research results on prediction, early detection, screening practices and diagnostic methods and tools, including via personalised and digital approaches.
• Medical and non-medical health professionals and technology developers have an increased knowledge, awareness and capacity to uptake and deliver effective and innovative approaches for risk prediction, early detection, screening and health management strategies, such as Virtual Human Twins (VHT)[1] or Artificial Intelligence (AI)-based applications. This involves supporting, strategic foresight, improving health literacy and cross-sectoral knowledge exchange and collaboration to drive innovation in personalised prevention and cardiovascular risk prediction.
• Healthcare providers and policymakers have an improved knowledge base to inform future strategies for early detection and prevention of CVDs, with specific attention to women and vulnerable groups, through research on personalised risk prediction approaches that consider multiple and interacting risk factors (e.g. genetic predisposition, environmental pollutants, diet, lifestyle habits, multimorbidity, sex and gender).

Scope:

CVDs are the main cause of death in the EU, with over 1.7 million deaths annually, costing about EUR 282 billion, or 11% of the healthcare budget[2]. With projections showing a rise in CVD prevalence and mortality by 2050 due to an aging population, the Commission is preparing a comprehensive EU Cardiovascular Health (CVH) plan[3] to support Member States in their efforts to reduce the burden of CVDs. The proposal is expected to support prevention, early detection, including via digital and personalised approaches.

Applicants should take stock of research and innovation results to identify gaps and set up a plan for a Strategic Research and Innovation Agenda (SRIA) on CVDs, with the final aim of leveraging research and innovation results to improve risk prediction, early detection and screening practices for CVDs and associated comorbidities, especially obesity and diabetes, across the EU and Associated Countries. This initiative addresses the pressing need to translate existing innovations and promising research results into implementable protocols that enhance prevention, diagnosis, and health outcomes for diverse populations. By fostering collaboration and integrating digital tools and methods, proposals will support the future EU CVH plan, building and aligning with future and ongoing activities, including the European VHT Initiative, the 1+Million Genomes Initiative[4], Tech Foresight/Horizon scanning activities[5] and actions funded under the EU4Health Programme (2021-2027)[6] and the Digital Europe Programme[7].

Proposals should include all the following activities:

• Conduct a comprehensive review at national, EU, and international levels of existing cardiovascular research and innovative healthcare solutions, potentially linked with associated comorbidities, to identify gaps and areas where future integration into health systems can have the greatest impact. The mapping should build upon existing EU-level reviews and pay particular attention to sex- and gender-related gaps, including under-representation in studies and differences in risk, diagnosis, and treatment. Such insights will inform subsequent policy actions and implementation initiatives under other funding programmes.
• Create a detailed report outlining the barriers to effective personalised prediction, screening and prevention in cardiovascular health, providing recommendations to overcome these challenges.
• Develop a SRIA on CVDs and associated comorbidities aiming to improve personalised prevention, prediction and screening and to inform research funders and stakeholders, including relevant EU and national initiatives. The agenda will include stakeholder validation and adoption pathways. Support the development of personalised prevention and care pathways and the role of digital interventions, based on genomics, VHTs and AI-driven methods in line with the European Health Data Space (EHDS)[8] Regulation, to enhance precision in early detection and health management. Where applicable, the mapping of existing practices such as biomarkers for diagnosis, monitoring in patients, and stratification of patient groups should be considered.
• Integrate sex and gender-related variables, age, racial or ethnic origin[9], socio-economic, lifestyle and behavioural factors, genetic predisposition into research design, data collection and analysis, to ensure inclusive and generalisable findings enhancing the effectiveness of screening, diagnostic, and prevention strategies across diverse population groups.
• Organise high-impact, targeted events with clear objectives to promote a multi-sectorial approach, fostering collaboration among healthcare providers, researchers, civil society, patients' organisations, and policymakers
• Work with health experts to develop the capacities for implementing standardised screening protocols and methods.
• Develop a comprehensive dissemination strategy and stakeholder engagement plan to share findings and promote the results, utilising online platforms and social media to reach a broad audience. Complement with long-term engagement mechanisms such as policy briefings or partnerships with EU-level dissemination networks.

The applicants should ensure adequate involvement across the project lifespan of all relevant stakeholders and value chain actors including industry, healthcare professionals, scientists, patients’ associations to ensure performance and sustainability and maximise the final impact.

This topic requires the effective contribution of social sciences and humanities (SSH) disciplines and the involvement of SSH experts and institutions, in order to meaningfully enhance the societal impact of the related research activities.

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