💰 Funding Details

Towards Precision Medicine: Platform for Transdiagnostic Stratification of Brain Dysfunction

Overview

The Innovative Health Initiative (IHI) Joint Undertaking under Horizon Europe is allocating up to €37,209,000 per project to develop an integrated, multimodal data platform capable of redefining diagnostics and treatment paradigms for CNS-related reward/motivation and impulsivity (RM&I) symptom domains across psychiatric, neurodegenerative and somatic disorders.

Key Elements

- Call Identifier: HORIZON-JU-IHI-2025-11-01-two-stage

- Type of Action: HORIZON-JU-RIA (Research & Innovation Action)

- Submission Model: Two-stage (20-page short proposal ➜ 50-page full proposal)

- Opening Date: 17 Jun 2025

- Stage 1 Deadline: 09 Oct 2025, 17:00 CET

- Stage 2 Deadline: 29 Apr 2026, 17:00 CET

Expected Impacts

1. Data platform for precision medicine – a sustainable, AI-ready repository linking behaviours, symptoms and quantitative biomarkers.

2. Advanced mechanistic understanding – clarification of the biology driving RM&I symptoms, catalysing novel therapeutics and diagnostics.

3. Improved patient outcomes & stigma reduction – personalised, integrated care across disorders, earlier intervention, reduced stigma.

4. Healthcare system efficiency – precision treatments that lower avoidable costs and boost productivity.

5. Policy alignment – direct contribution to the European Health Data Space, AI Act, Mental Health Communication and Healthier Together NCD initiative.

Eligibility Snapshot

- Standard Horizon Europe eligibility rules apply.

- *Exception:* Legal entities established in your country (e.g., UK, Canada) are eligible for funding under this topic.

- Minimum consortium: 3 independent legal entities from 3 different eligible countries, at least one established in an EU Member State.

Indicative Budget & Funding Rate

- Total topic budget: ~€37.2 M

- EU funding rate: 100 % of eligible direct costs + 25 % flat-rate indirect costs (HORIZON-AG MGA).

Strategic Fit

The topic is positioned to be a flagship for data-driven, biology-anchored precision medicine in CNS disorders, serving as a template for other disease areas once validated.

📊 Evaluation Criteria

What Evaluators Look For

1. Excellence

* Soundness of transdiagnostic scientific approach; novelty of biomarker strategy.

* Robust AI/ML methodology and data governance compliant with GDPR & FAIR.

2. Impact

* Credible pathway to regulatory/HTA qualification.

* Clear sustainability plan for open-access platform beyond project.

* Alignment with EU policies (EHDS, AI Act, Mental Health).

3. Quality & Efficiency of Implementation

* Balanced consortium (academia, SMEs, industry, patient orgs).

* Realistic work-plan, risk and data-quality management (Data Quality Assessment Committee).

📝 Application Strategy

Strategic Application Guide

1. Concept Positioning

1. Transdiagnostic focus: Centre the proposal on RM&I symptom biology rather than DSM/ICD categories.

2. Platform architecture: Layered design – data ingestion, harmonisation, analytics, clinical decision support.

3. Priority disorders: Demonstrate deep use-cases in Alzheimer’s disease, major depressive disorder and obesity while showing scalability to others.

2. Consortium Design

- Clinical depth: University hospitals with large CNS cohorts & biobanks.

- Tech excellence: AI/ML SMEs, FAIR data architects, cybersecurity providers.

- Patient voice: At least two patient organisations covering psychiatric and neurodegenerative perspectives.

- Industry pull: Pharma/Med-tech partners to co-define biomarker qualification pathways.

- Health-economics & ethics: Experts in cost-effectiveness modelling, data governance, and compliance with the EHDS & AI Act.

3. Work-Package (WP) Blueprint

1. WP1 – Governance & Ethics (incl. DPO, AI ethics board).

2. WP2 – Data Harmonisation & Interoperability (OMOP, FHIR, GDPR-by-design).

3. WP3 – Multi-modal Biomarker Discovery (imaging, –omics, digital phenotyping).

4. WP4 – AI-driven Stratification & Validation (federated learning, external validation sets).

5. WP5 – Clinical Demonstration Studies (adaptive design trials in AD, MDD, obesity).

6. WP6 – Health-Economic & Policy Impact (budget impact simulation, reimbursement pathways).

7. WP7 – Exploitation, Sustainability & Outreach (open science, SME acceleration, spin-offs).

4. Stage-Specific Focus

- Stage 1 (20 pages): Crystal-clear vision, consortium credibility, novelty, expected impact, alignment with IHI KPIs.

- Stage 2 (50 pages): Deep methodology, risk mitigation, data-management plan, KPI dashboard, detailed budget, exploitation & IP strategy (incl. JU right to object clause).

5. Evaluation Excellence Checklist

- Excellence (0–5): Solid scientific grounding, transformative concept, sex-/gender-/age-analysis.

- Impact (0–5): Quantified patient & budget benefits, alignment with EU policies, credible exploitation plan.

- Quality & Efficiency (0–5): Robust project structure, resources, risk & contingency table, TRL advancement logic.

💡 Success Factors

Holistic Data Architecture

Design a **federated, FAIR-compliant data lake** with real-world clinical, imaging, –omics and digital phenotyping streams to maximise discovery power and privacy.

Regulatory Road-Mapping

Embed **EMA scientific advice** and **IVDR alignment** milestones to fast-track biomarker qualification and diagnostic approval.

End-to-End AI Governance

Adopt **TRUST-AI** principles (transparency, robustness, usability, safety, traceability) and pre-emptively align with the EU AI Act’s risk-based framework.

Early Health-Economic Validation

Simulate cost-offset scenarios using country-level DRG tariffs to prove the platform’s capacity to **reduce €-per-QALY** and persuade payers.

Scalable Sustainability Model

Present a blended revenue approach—open science tier, subscription APIs for pharma, and a **your country-wide public procurement** pilot—to ensure longevity.

Robust Risk & Contingency Matrix

Map each critical risk (e.g., data-sharing refusal, algorithmic bias) to quantified likelihood/impact scores and **SMART mitigation actions**.

❌ Common Mistakes to Avoid

Focusing on a Single Disorder

The call explicitly demands **transdiagnostic** relevance. Concentrating solely on Alzheimer’s disease *or* major depressive disorder without showing cross-disorder scalability scores poorly on impact.

Neglecting Data Interoperability Standards

Submissions that omit **OMOP, FHIR or GA4GH** alignment fail to convince evaluators that the platform can integrate with the forthcoming European Health Data Space.

Underestimating Ethical & Legal Complexity

Ignoring GDPR, EHDS, AI-Act conformity or lacking a Data Protection Officer is a red flag that triggers low scores under ‘Quality & Efficiency of the Implementation.’

Tokenistic Patient Involvement

Listing a patient group without clear roles, co-creation activities, or budget allocation is considered superficial and undermines the societal impact narrative.

Vague Exploitation & Sustainability Plan

Evaluators need concrete post-grant models (e.g., freemium data-access, public–private foundation) to believe the platform will survive beyond EU funding.

Insufficient Industrial Commitment

Failing to include at least one pharma/med-tech partner weakens the value-chain coverage and the credibility of biomarker qualification and market uptake.

Towards precision medicine: platform for transdiagnostic stratification of brain dysfunction

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