Summary
- Profile Type
- Research & Development Request
- POD Reference
- RDRLU20260626015
- Term of Validity
- 23 July 2026 - 23 July 2027
- Company's Country
- Luxembourg
- Type of partnership
- Research and development cooperation agreement
- Targeted Countries
- Belgium
- Netherlands
- France
- Sweden
- Serbia
- Denmark
- Hungary
- Faroe Islands
- Italy
- Croatia
- Estonia
- Georgia
- Austria
- Poland
- Finland
- Moldova
- Lithuania
- Cyprus
- Iceland
- Slovakia
- Germany
- Malta
- Albania
- Portugal
- Romania
- Bulgaria
- Greece
- Switzerland
- Luxembourg
- North Macedonia
- Israel
- Slovenia
- Ukraine
- Latvia
- Bosnia and Herzegovina
- Czechia
- Ireland
- Spain
- Montenegro
- Kosovo
- Tunisia
- Norway
- United Kingdom
- Egypt
- Türkiye
General information
- Short Summary
- A Luxembourg-based digital health company seeks European clinical partners for an EIC Pathfinder Challenge project. The objective is an observational multi-center sub-study tracking maternal food, sleep, activity, stress, voice, and gut microbiome data. Clinical partners will drive first-trimester patient recruitment and longitudinal biobanking to train machine-learning models that predict gestational diabetes, preeclampsia, depression, and lifelong healthy ageing trajectories.
- Full Description
-
This project addresses a critical gap in healthy ageing biology: the lack of early-lifespan human models that can predict long-term physiological decline before chronic, age-related diseases appear. Standard ageing clocks measure slow-drift biological degradation in post-reproductive populations. Recent literature, by contrast, shows that human pregnancy acts as a naturally occurring, time-compressed and hormonally amplified stress test of the core hallmarks of ageing.
The project aims to build an investigational, low-maturity machine learning engine, at Technology Readiness Level 1 to 3 (TRL 1-3), to map this stress window. Rather than deploying a commercial app or consumer intervention, it establishes a non-interventional, multi-modal biological screening platform.
The central data-processing engine uses a late-fusion neural network with gated attention, designed to ingest asynchronous digital and multi-omic data streams. These fall into two complementary types.
- The first is high-frequency edge data: vocal biomarkers, actigraphy-based sleep patterns, physical activity, self-reported food logs and stress metrics.
- The second is discrete biological data: shotgun gut metagenomics, serum inflammaging panels and plasma epigenetic clocks, sampled every three months. The algorithm will then evaluate cross-talk across six hallmarks of ageing defined by López-Otín and colleagues (2023): dysbiosis (#12), chronic inflammation or inflammaging (#11), epigenetic alteration (#3), deregulated nutrient sensing (#6), mitochondrial dysfunction (#7) and cellular senescence (#8). - Advantages and Innovations
-
The primary innovation is to transform the perinatal window from a period of clinical passivity into a predictive healthy-ageing optimisation event. Unlike single-modality ageing clocks or late-stage reactive screening, the project will use a multi-target machine learning engine to integrate digital behaviour with biological data. By capturing the cross-talk between nutrient sensing, mitochondrial fitness, cellular senescence and the gut microbiome, the model maps systemic biological ageing under physiological pressure.
Methodologically, the engine is built for rigour. It avoids data leakage through strict subject-disjoint and visit-disjoint cross-validation partitions; it uses TreeSHAP/DeepSHAP so that predictions map transparently back to specific cellular hallmarks; and it applies temperature scaling for tight calibration. Together these measures make the model's outputs both interpretable and trustworthy.
Women with a history of gestational diabetes (GDM) face up to a ten-fold higher relative risk of progressing to type 2 diabetes, associated with a life-expectancy gap of at least six years. By delivering a validated, TRL1-3, hallmark-anchored stratification signature, the project will provide an ultra-early warning system. It would allow developers of healthy-ageing interventions to stratify and select cohorts for preventative trials decades before chronic metabolic and cardiovascular disease takes root, with the potential to reduce long-term healthcare costs and extend maternal health-span. - Technical Specification or Expertise Sought
- We are seeking clinical research institutions, university hospital networks or maternal-foetal medicine centres with access to first-trimester cohorts and the capacity to run longitudinal observational perinatal protocols.
- Stage of Development
- Under development
- Sustainable Development Goals
- Goal 3: Good Health and Well-being
- IPR status
- Secret know-how
Partner Sought
- Expected Role of a Partner
-
The selected clinical partner will be responsible for the setup, execution and sampling governance of their local sub-study site.
Their core operational responsibilities are to:
- Secure ethical approval and site activation - prepare and submit local research ethics committee applications by Month 2, achieving full site activation by Month 6.
- Recruit the cohort - deploy recruitment strategies across their hospital or clinical network to enrol a cohort of first-trimester pregnant volunteers.
- Run the research protocol - administer the multi-modal SOPs and support participant compliance with data collection (food intake, wearable actigraphy, heart-rate-variability stress metrics and smartphone vocal journals).
- Manage longitudinal sampling - coordinate the collection, processing, freezing and secure storage of stool and blood samples across the four pre-specified timepoints (gestational weeks 8 and 24; postpartum months 3 and 12).
- Safeguard data at the edge - enforce strict data-minimisation and privacy-preserving protocols, ensuring human reads are stripped from metagenomic sequences and audio features are processed in line with GDPR Article 9 before any cross-border transfer.
- Join the EIC Pathfinder portfolio activities - contribute representatives to Working Group 3 (Ethical, Legal and Societal Implications) to collaborate on cross-project work on informed consent, reproductive equity and biological-data protection in vulnerable maternal cohorts. - Type and Size of Partner
- University
- R&D Institution
- SME 50 - 249
- Type of partnership
- Research and development cooperation agreement
Call details
- Framework program
- Horizon Europe
- Call title and identifier
-
HORIZON-EIC-2026-PATHFINDERCHALLENGES-01-02 - Biotechnology for Healthy Ageing
- Submission and evaluation scheme
-
Single-stage submission with remote evaluation panel and cross-cutting portfolio considerations.
- Anticipated project budget
-
€3,000,000 – €3,500,000
- Coordinator required
-
Yes
- Deadline for EoI
- Deadline of the call
- Project duration in weeks
-
208
- Web link to the call
- https://ec.europa.eu/info/funding-tenders/opportunities/portal/screen/opportunities/topic-details/HORIZON-EIC-2026-PATHFINDERCHALLENGES-01-02?order=DESC&pageNumber=1&pageSize=50&sortBy=startDate&keywords=biotechnology%20for%20healthy%20ageing&isExactMatch=
- Project title and acronym
-
Maternal Healthy Ageing Trajectories via Multi-Modal Perinatal Observation (VITA-DYAD)
- Horizon Europe
Dissemination
- Technology keywords
- 06003001 - Bioinformatics
- 06002008 - Microbiology
- 02009007 - Artificial intelligence applications for cars and transport
- 06001005 - Diagnostics, Diagnosis
- 06001002 - Clinical Research, Trials
- Market keywords
- 02007016 - Artificial intelligence related software
- 02007012 - Medical/health software
- 05007006 - Computer-aided diagnosis and therapy
- Sector Groups Involved
- Health
- Targeted countries
- Belgium
- Netherlands
- France
- Sweden
- Serbia
- Denmark
- Hungary
- Faroe Islands
- Italy
- Croatia
- Estonia
- Georgia
- Austria
- Poland
- Finland
- Moldova
- Lithuania
- Cyprus
- Iceland
- Slovakia
- Germany
- Malta
- Albania
- Portugal
- Romania
- Bulgaria
- Greece
- Switzerland
- Luxembourg
- North Macedonia
- Israel
- Slovenia
- Ukraine
- Latvia
- Bosnia and Herzegovina
- Czechia
- Armenia
- Ireland
- Spain
- Montenegro
- Kosovo
- Tunisia
- Norway
- United Kingdom
- Egypt
- Türkiye