Towards precision medicine: platform for transdiagnostic stratification of brain dysfunction

The HORIZON-JU call, titled "Towards precision medicine:platform for transdiagnostic stratification of brain dysfunction," is part of the Horizon Europe Programme under the Innovative Health Initiative (IHI) and features a total budget of €20.2 million. This initiative encourages collaborative research and innovation focused on Central Nervous System disorders, including Alzheimer's disease, major depressive disorder, and obesity.

Eligible applicants for this funding opportunity include universities, research institutions, small and medium-sized enterprises, patient organizations, and sometimes larger companies. Notably, legal entities from the UK and Canada are also eligible under this call. The funding type is a non-repayable grant distributed through the Horizon Europe framework.

A consortium is required to apply, necessitating public-private partnerships that involve academia, industry, and healthcare stakeholders. The geographic eligibility encompasses EU member states, associated countries, and low to middle-income countries.

The application process consists of two stages. The first stage involves a short proposal due by October 9, 2025, and the second stage requires a full proposal due by April 29, 2026. Funding is designed to cover project costs, including personnel and equipment, with industry partners mandated to contribute at least 45% of the total budget.

The main objective of the call is to develop a sustainable data platform that integrates various multimodal datasets to improve the diagnosis and treatment of brain disorders. This includes utilizing AI and machine learning to analyze data and identify novel biomarkers. The project seeks not only to enhance understanding of the biological bases of these disorders but also to facilitate the creation of clinical guidelines and regulatory frameworks.

Successful applicants are expected to implement a comprehensive approach that includes collecting new clinical datasets, conducting pilot clinical case studies, and engaging with stakeholders, including patients and healthcare professionals, to ensure inclusivity and equitable practices throughout the project.

In summary, the initiative aims to transform mental health care through a holistic and collaborative framework that advances precision medicine. The expected outcomes emphasize improved treatment paradigms, enhanced patient care quality, and efficient use of healthcare resources while maintaining ethical standards. The entire framework is designed to be adaptive to future innovations and encourages ongoing open access to the developed platform for continued research.

The HORIZON-JU call, titled "Towards precision medicine:platform for transdiagnostic stratification of brain dysfunction," is a HORIZON JU Research and Innovation Action (RIA) under the Horizon Europe Programme, specifically the Innovative Health Initiative JU Call 11 (HORIZON-JU-IHI-2025-11-two-stage). It employs a two-stage submission deadline model. The call opens on June 17, 2025, with the first stage deadline on October 9, 2025, at 17:00:00 Brussels time, and the second stage deadline on April 29, 2026, at 17:00:00 Brussels time. The total budget allocated to this topic is €20,202,000, and it is expected that around 1 grant will be awarded.

The expected impacts of this action are:

A comprehensive, sustainable data-driven health platform for precision medicine, linking behaviors and symptoms to quantitative biological markers, refining diagnostic frameworks and treatment paradigms for Central Nervous System (CNS)-driven symptoms. This platform aims to serve as a model for other disease areas needing biology-driven precision medicine.

Advancing mechanistic understanding of CNS transdiagnostic symptoms to expedite the identification of novel and more effective precision therapies, boosting European industry competitiveness and galvanizing innovation in diagnostics.

Significant improvement in care quality and health outcomes for people within the Reward/Motivation & Impulsivity (RM&I) driven relevant disorders, including healthcare innovations arising from improved understanding of the relationship between psychiatric and physical health and their underlying biology, reducing stigma and providing opportunities for early intervention.

Efficiency in the healthcare system through precision treatments that reduce avoidable waste in healthcare resources, leading to overall cost reduction, higher productivity, and a positive economic impact on the European health care budget.

The expected outcomes of this action are:

A sustainable and collaborative large, multimodal data platform that can identify novel transdiagnostic candidate markers and endpoints for the symptom domains of reward/motivation (including anhedonia) and impulsivity (RM&I) in neuropsychiatric, neurodegenerative, and physical health disorders, including Alzheimer’s disease (AD), major depressive disorder (MDD) and obesity (priority areas), substance use and associated disorders, schizophrenia, bipolar disorder, borderline personality disorder and Parkinson’s disease.

Identification of novel transdiagnostic candidate markers and endpoints, progressed towards validation and applied in drug discovery to increase probability of success (PoS).

A clear roadmap to achieve full validation of candidate markers and endpoints by regulatory and health technology assessment (HTA) bodies, development of clinical best-practice guidelines, and recommendations to current diagnostic classifications to expedite the adoption of precision medicine.

A greater understanding of the biological foundations of RM&I symptom domains and their role in AD, MDD, obesity and other relevant disorders, enabling the generation of novel therapeutic approaches by industry.

Closer alignment between psychiatry, neurology, and physical health disciplines to enable dialogue between healthcare professionals (HCPs) and other medical specialists to optimise outcomes, particularly for individuals with complex healthcare needs and comorbidities.

The objectives of this topic are:

Adapt and extend an existing federated data platform that is sustainable, enabling collaborative curation, access and analysis of clinical datasets and samples. Consolidate existing multimodal datasets and samples from cohorts with relevant disorders into the adapted platform.

Collect additional new clinical datasets and samples to address gaps and integrate these into the adapted platform.

Test hypotheses for candidate markers and endpoints within a defined context (e.g. patient selection, diagnosis, or treatment monitoring) in a transdiagnostic patient population presenting symptom domains of RM&I, including those with AD, MDD, and obesity.

Establish a collaborative platform to bring together people with lived experience (LE), HCPs, regulators, HTA bodies and payers to achieve consensus on the value of candidate markers and endpoints, how to operationalise them into new diagnostic and treatment frameworks and achieve readiness in the healthcare system.

Activities under objective 1 include:

Collating existing multimodal, longitudinal and transdiagnostic datasets at an individual level, including relevant parameters. These datasets can come from public or private databases, observational studies, clinical trials, real-world evidence (RWE) studies, biobanks, electronic health records, registries, and/or other digital health technologies and platforms. Applicants must include a strategy to utilize relevant data from the European Platform for Neurodegenerative Diseases (EPND) catalogue as much as possible as well as other relevant datasets available from previous projects (including pre-clinical data).

Relevant multimodal datasets ideally include as many as possible from the following:neurophysiology data (e.g. electroencephalography (EEG), magnetoencephalography (MEG)), brain imaging data (e.g. functional magnetic resonance imaging (fMRI), MRI), qualitative subjective assessments, behavioural data, real-world data, medical claims and billing data, routine clinical data (from medical and psychological assessments including data on metabolic status), physiological/activity monitoring data (polysomnography, actigraphy, digital data from wearables, etc.), speech/language data, patient reported outcome data (e.g. questionnaires), molecular biodata (e.g. “-omics”), and potentially data gained via therapeutic protocols (drugs, neuromodulation (deep brain stimulation, transcranial magnetic stimulation, transcranial functional ultrasound, etc.)). Biological samples (e.g. blood, urine, stools, cerebrospinal fluid) from biobanks should be leveraged. Datasets should be from individuals with relevant disorders as well as healthy controls.

Proposing a strategy to integrate and connect the datasets from different sources.

Outlining an approach to inclusive and equitable practices, including data representation, including but not limited to gender, ethnicity, and age (e.g. paediatric and adolescent populations).

Adapting and extending a federated data platform by building on existing infrastructures proven effective in PPPs, including the AD Workbench and the EPND hub. The adapted platform should leverage available resources (including standard operating procedures) from EPND. The adapted platform must be scalable and adaptable to curate high-quality, multimodal, retrospective, prospective and longitudinal data. It must enable data/sample discovery, access, and support AI analysis, while ensuring interoperability with other global data platforms.

Ensuring high data quality by verifying the robustness of methodologies before integration into the adapted platform, potentially through a Data Quality Assessment Committee.

Implementing fair and transparent governance for data- and sample-sharing including model interpretability, data provenance, and traceability of AI decision-making processes. Applicants must explain how they will develop a consensus on data sharing principles, complying with legal and ethical standards (e.g. General Data Protection Regulation (GDPR) and intellectual property rights (IPR)) and ensuring robust protection of data volunteers' rights. For example, leveraging the Data Sharing Playbook and setting up a Data Access Review Committee.

Reviewing the collated dataset to identify key gaps and develop a strategy to guide new data collection under Objective 2.

Identifying potential algorithms for activities under 3.3 in Objective 3.

Ensuring platform sustainability by creating a strong value proposition and user ecosystem beyond the consortium, with a clear strategy for a long-term, AI-powered platform accessible to the broader research community, including the healthcare industry. Relevant activities need to be in place from the start of the action.

Activities under objective 2 include:

Collecting new prospective multimodal and ideally longitudinal data from transdiagnostic cohorts, focusing on individuals affected by RM&I abnormalities in the relevant disorders, and ideally also collect biological samples. The datasets should close data gaps identified under 1.8 and be integrated into the adapted platform, meeting the same criteria described in objective 1.

Continuing to recognise and fill data gaps to expand and maintain the adapted data platform, keeping it current with technological and scientific advancements. Whenever appropriate, utilise AI/ML, such as synthetic data generation, image analysis, natural language processing etc., to enhance the dataset.

Continuing identification of potential algorithms for activities under 3.3 in Objective 3.

Activities under objective 3 include:

Proposing an initial pilot clinical case study designed to test a scientifically robust and data-supported hypothesis on candidate markers and/or endpoints in RM&I symptom domains during the project’s initial year. It must include transdiagnostic populations from AD, MDD, and obesity. The case study must include as a minimum neurophysiological data (e.g. EEG or MEG) and brain imaging data (e.g. MRI, fMRI) from each subject. In addition, datasets should include as many parameters as possible from the list described in 1.2. The precise scope of the initial clinical case study will be developed by the full consortium during the preparation of the full proposal.

Preparing a systematic literature review (white paper) of the available potential markers in RM&I symptom domains in relevant disorders to support hypothesis generation and subsequent testing within the first 6 months. This should be kept up to date throughout the action.

Applying suitable statistical methods, advanced computational analytics (including, whenever appropriate, AI/ML as part of the statistical/analytical toolbox), modelling, and simulation across the multimodal data in the adapted platform to cluster biologically similar subjects across disorders/diseases, stratified independently of their conventional diagnostic classification. This should enable to identify and confirm clinically significant, quantitative candidate markers for RM&I symptom domains in relevant disorders, incorporating hypothesis-driven and data-driven approaches. It should also establish the foundation for a new transdiagnostic framework based on phenotypes/biotypes to enable detection of factors for susceptibility, risk stratification, diagnostic precision, disease monitoring, treatment response prediction, and overall patient outcomes. In addition, it should elucidate the biological underpinnings of the relationship between psychiatric and physical health (e.g. for obesity, understanding the interplay between metabolic disturbances, mental health and eating behaviours).

Testing putative transdiagnostic markers and endpoint hypotheses derived from 3.2 and 3.3 through additional non-sequential pilot clinical case studies, incorporating insights from stakeholder consultations as mentioned in objective 4. These case studies must test the same transdiagnostic marker/endpoints in separate pre-defined patient populations in two or more of the relevant disorders to strengthen the transdiagnostic approach. As a preference, the three priority disorders should be included in at least one study each as a lead indication. For instance, one study with AD, one with MDD and one with obesity as the lead indication, each including at least one additional relevant disorder. Each study must include neurophysiological and brain imaging data and include as many other parameters as possible from the list outlined under 1.2. Studies must be powered sufficiently to allow analyses both within and across the included disorders. All results must be integrated into the adapted platform. The studies should enhance the platform's ability to accelerate hypothesis testing of new candidate markers and endpoints within a defined context of use (e.g. patient selection, diagnosis, or treatment monitoring) in representative patient populations. These studies must not involve the development of new in vitro diagnostic tools or digital sensors. The resulting evidence from pilot case studies (including the initial pilot clinical study under 3.1) should: be verifiable and applicable for patient stratification and/or monitoring in future clinical trials; demonstrate clinical utility to foster new patient pathways and clinical guidelines; contribute to bridging the gap between health care needs and capacity.

Activities under objective 4 include:

Creating an efficient collaborative platform to support seamless communication and collaboration among key stakeholders in the field of the relevant disorders. This includes innovators, researchers, clinicians, people with LE, carers, patient advocates, HCPs, regulators, scientific societies, HTA bodies, payers, and policy makers to collectively define and implement a new framework for the diagnosis and treatment of these disorders.

Forming advisory/working groups comprising different stakeholders to support activities under objectives 1, 2 and 3, and co-create solutions. Ensure active and meaningful participation of people with LE, carers, and advocacy organisations throughout the activities and governance.

Engaging with regulators (via experts with relevant expertise), e.g. EMA and/or national competent authorities, proactively initiating early consultations as appropriate. This should set the basis for continuation towards full validation of markers and endpoints beyond the action. Applicants are expected to consider the potential regulatory impact of the results and as relevant, develop a regulatory strategy and interaction plan early on to define a strategic approach to evidence collection and analysis where feasible (including case studies under objective 3) for generating appropriate evidence, as well as engaging with regulators in a timely manner (e.g. national competent authorities, EMA Innovation Task Force, qualification advice). Similarly, appropriately engage with HTA bodies and payers on the value of new transdiagnostic framework, candidate markers and endpoints when used to support claims of effectiveness of new therapies, paving the way for future reimbursement.

Crafting evidence-based clinical guidelines through consultations with stakeholders, including people with LE, regulators, HTA bodies, payers, and medical organisations. Achieve consensus on best practices for implementing the new transdiagnostic framework. Develop recommendations and provide proposals for updates to the classification of disorders.

Designing and implementing a comprehensive training programme for HCPs to adopt the new transdiagnostic framework. Create educational materials and implement trainings for people with LE, families and carers in multiple languages, ensuring readiness across the healthcare system for the paradigm shift in healthcare delivery throughout Europe and helping to reduce stigma.

The scope of this call emphasizes a transdiagnostic approach to health disorders with Central Nervous System (CNS)-driven symptoms, moving away from the current DSM-5 / ICD-11 codes. It focuses on the common underlying biology of RM&I symptom domains across relevant disorders. The call seeks to build on an existing federated data platform to consolidate, curate, link and analyse robust, multimodal datasets from relevant patient populations. Activities related to building a new platform or a biorepository from scratch are out of scope. The data platform must enable data/sample discovery, access, and support advanced computational analysis including artificial intelligence (AI)/ machine learning (ML) technologies while ensuring interoperability with other global data platforms to illuminate the biological basis of the RM&I symptom domains and identify related candidate markers and endpoints. The hypotheses will be prospectively tested in clinical case studies focusing on but not limited to AD, MDD, and obesity. Post-project, the platform will be available as open access for ongoing research and validation.

The call prioritizes collaboration with relevant stakeholders, including people with lived experience (LE), carers, HCPs, providers, regulators, HTA bodies and payers, to prepare the healthcare system for this transformative shift. Applicants must outline their approach to inclusive and equitable practices throughout the initiative, possibly through a risk register and appropriate mitigations.

The admissibility conditions include proposal page limits:20 pages for RIA short proposals at stage 1 and 50 pages for RIA full proposals at stage 2. Eligible countries are described in Annex B of the Work Programme General Annexes, with specific provisions for non-EU/non-Associated Countries. Other eligibility conditions are described in Annex B of the Work Programme General Annexes and in the “Conditions of the Calls for proposals and Call management rules” section of the IHI JU Work Programme (WP). Financial and operational capacity and exclusion criteria are described in Annex C of the Work Programme General Annexes. Evaluation and award criteria, scoring and thresholds are described in Annex D of the Work Programme General Annexes and in the “Conditions of the Calls for proposals and Call management rules” section of the IHI JU Work Programme (WP). Submission and evaluation processes are described in Annex F of the Work Programme General Annexes and the Online Manual. The indicative timeline for evaluation and grant agreement is described in Annex F of the Work Programme General Annexes. Legal and financial set-up of the grants is described in Annex G of the Work Programme General Annexes.

Specific conditions include that conditions on Availability, Accessibility and Affordability (3A) do not apply to this topic, and the JU has the right to object to transfer/exclusive licensing. Legal entities established in the UK and Canada are eligible to receive funding for this topic.

Applicants must use the provided templates and annexes, which are available for download in the submission system of the Funding and Tender Opportunities portal. Compulsory annexes include the Annex: Type of Participants (for stage 1), Annex to the budget and type of participants (for stage 2), Declaration of in-kind contribution commitment, and Essential information for clinical studies. An optional annex is In-kind contributions to additional activities (IKAA).

In summary, this call aims to foster precision medicine for CNS disorders by creating a sustainable data platform, advancing mechanistic understanding, improving patient outcomes, and enhancing healthcare system efficiency. It encourages collaboration among diverse stakeholders and emphasizes ethical and equitable practices. The call provides funding for research and innovation actions, with specific eligibility criteria and a two-stage submission process. The total budget for this topic is €20,202,000, with an expectation of awarding approximately 1 grant.

Eligible Applicant Types:The eligible applicant types are not explicitly defined in the provided text. However, based on the context of Horizon Europe Research and Innovation Actions (RIA) and the Innovative Health Initiative (IHI) JU, eligible applicants typically include a consortium of various legal entities such as: startup, SME, large enterprise, university, research institute, nonprofit, government, public-private partnership, or other relevant organizations involved in health research and innovation. The call text mentions "innovators, researchers, clinicians, people with lived experience (LE), carers, patient advocates, HCPs, providers, regulators, scientific societies, HTA bodies and payers, and policy makers" as stakeholders, implying that these groups or their representative organizations are potential applicants or partners.

Funding Type:The funding type is a grant, specifically a HORIZON Action Grant Budget-Based [HORIZON-AG], under the HORIZON JU Research and Innovation Actions (HORIZON-JU-RIA).

Consortium Requirement:The opportunity requires a consortium. The text mentions "public-private partnership (PPP)" and emphasizes the need for a "collaborative platform" and "consortium" to achieve the objectives. The requirement for a 45% industry contribution further suggests a consortium structure.

Beneficiary Scope (Geographic Eligibility):The geographic eligibility is primarily focused on EU member states and associated countries within the Horizon Europe framework. However, there are specific exceptions, as legal entities established in the UK and Canada are also eligible to receive funding under this particular topic. The general conditions mention Annex B of the Work Programme General Annexes, which further details eligible countries.

Target Sector:The program targets the health sector, specifically precision medicine, neuropsychiatry, neurodegenerative disorders, physical health disorders, drug discovery, diagnostics, and related areas. It focuses on Central Nervous System (CNS)-driven symptoms and the symptom domains of reward/motivation (including anhedonia) and impulsivity (RM&I). The initiative also aims to align psychiatry, neurology, and physical health disciplines. Specific areas include Alzheimer’s disease (AD), major depressive disorder (MDD), and obesity, as well as substance use disorders, schizophrenia, bipolar disorder, borderline personality disorder, and Parkinson’s disease. The program also involves data science, artificial intelligence (AI), and machine learning (ML) for data analysis and platform development.

Mentioned Countries:United Kingdom, Canada.

Project Stage:The project stage targets research, development, and validation, with an emphasis on adapting and extending existing data platforms and testing hypotheses through clinical case studies. The focus is on progressing candidate markers and endpoints towards validation and application in drug discovery and clinical practice. Therefore, the project stage encompasses development, validation, and demonstration.

Funding Amount:The budget for the topic HORIZON-JU is €20,202,000. The budget for the other topics HORIZON-JU-IHI-2025-11-04-two-stage, HORIZON-JU-IHI-2025-11-02-two-stage, HORIZON-JU-IHI-2025-11-03-two-stage and HORIZON-JU-IHI-2025-11-05-two-stage is €37,209,000. The contribution for each of these topics is around €8,825,000, €7,127,000, €8,906,000 and €12,351,000 respectively.

Application Type:The application type is an open call with a two-stage submission process.

Nature of Support:The beneficiaries will receive money in the form of a grant to support their research and innovation activities.

Application Stages:The application process involves two stages: a short proposal in the first stage and a full proposal in the second stage.

Success Rates:The success rates are not explicitly mentioned, but the indicative number of grants suggests that for the topic HORIZON-JU, one grant will be awarded, and for the other topics HORIZON-JU-IHI-2025-11-04-two-stage, HORIZON-JU-IHI-2025-11-02-two-stage, HORIZON-JU-IHI-2025-11-03-two-stage and HORIZON-JU-IHI-2025-11-05-two-stage, one grant will be awarded for each topic.

Co-funding Requirement:The call requires a 45% industry contribution, indicating a co-funding requirement. This can be in the form of in-kind contributions or financial contributions from industry partners within the consortium.

Summary:This is a Horizon Europe Innovative Health Initiative (IHI) JU call for proposals focused on "Towards precision medicine: platform for transdiagnostic stratification of brain dysfunction." The call aims to fund research and innovation actions that will adapt and extend an existing federated data platform to improve the diagnosis and treatment of Central Nervous System (CNS) disorders, particularly Alzheimer’s disease, major depressive disorder, and obesity. The project requires a consortium of diverse stakeholders, including researchers, clinicians, industry partners, and patient representatives, to collaborate on consolidating and analyzing multimodal datasets, identifying novel biomarkers, and developing clinical guidelines. The funding is provided as a grant, and the application process involves a two-stage submission. The initiative seeks to transform healthcare by adopting a holistic, transdiagnostic approach, leveraging AI and machine learning, and prioritizing collaboration with stakeholders to prepare the healthcare system for a paradigm shift in the delivery of precision medicine. Legal entities from the UK and Canada are eligible for funding under this call. The budget for the topic HORIZON-JU is €20,202,000. The budget for the other topics HORIZON-JU-IHI-2025-11-04-two-stage, HORIZON-JU-IHI-2025-11-02-two-stage, HORIZON-JU-IHI-2025-11-03-two-stage and HORIZON-JU-IHI-2025-11-05-two-stage is €37,209,000. The contribution for each of these topics is around €8,825,000, €7,127,000, €8,906,000 and €12,351,000 respectively.