HEDIMED and HEAP both focus on human exposome assessment, combining environmental exposure data with biological markers and wearable sensing.
PIRKANMAAN HYVINVOINTIALUE
Finnish regional healthcare authority contributing clinical populations and health data to EU research on disease screening, exposome, and precision prevention.
Their core work
Pirkanmaan Hyvinvointialue is the regional wellbeing services authority for the Pirkanmaa region in Finland, headquartered in Tampere. It provides public healthcare and social services to approximately half a million residents, operating one of Finland's largest hospital districts. In EU research, the organization contributes clinical cohort data, patient populations, and real-world healthcare infrastructure to large-scale studies on disease prevention, screening, and exposome-health interactions. Their participation brings a critical bridge between population-level health data and translational research in areas ranging from cardiovascular disease to cancer screening.
What they specialise in
TAXINOMISIS (carotid artery stratification), RISCC (cervical cancer risk-based screening), and TO_AITION (immune-metabolic disease prediction) all centre on patient stratification.
RISCC applies predictive modelling to cervical cancer screening at population scale; HEDIMED runs prevention trials in birth cohorts.
TAXINOMISIS uses pharmacogenomics, HEDIMED applies multi-omics sensoring, and HEAP integrates metabolomics and microbiomics data.
HEAP deploys AI and big data platforms; RISCC develops digital applications for screening — both reflecting a shift toward computational health tools.
How they've shifted over time
Their earliest H2020 project (TAXINOMISIS, 2018) focused narrowly on clinical stratification for a single vascular condition using omics and computational modelling. From 2020 onward, the scope broadened dramatically: four projects launched simultaneously covering exposome research, immune-metabolic comorbidities, cancer screening, and wearable sensor platforms. The clear trajectory is from disease-specific clinical research toward population-wide, data-intensive prevention and screening — with growing emphasis on AI, big data infrastructure, and digital health tools.
Moving toward large-scale digital health infrastructure combining exposome data, AI analytics, and population screening — positioning themselves as a clinical data partner for precision prevention research.
How they like to work
Pirkanmaan Hyvinvointialue joins consortia exclusively as a participant, never as coordinator, which is typical for healthcare providers contributing clinical data and patient access rather than leading research design. With 67 unique partners across 20 countries in just 5 projects, they engage in large international consortia (averaging 13+ partners per project). This broad network suggests they are valued for their population data and clinical infrastructure rather than for niche technical expertise, making them accessible and experienced consortium partners.
An extensive European network spanning 67 unique partners across 20 countries, built through five large RIA consortia. Their reach is broad and pan-European, without visible geographic clustering, reflecting their role as a sought-after clinical data provider.
What sets them apart
As a major Finnish regional healthcare authority serving the Tampere metropolitan area, they offer something most research institutes cannot: direct access to real-world patient populations, longitudinal health records, and functioning clinical screening infrastructure. Their dual involvement in both exposome research (HEDIMED, HEAP) and disease screening (RISCC) creates a rare combination — they can contribute both environmental exposure data and clinical outcome data within the same organization. For consortium builders, this means a single partner that covers both the data generation and clinical validation sides of health research.
Highlights from their portfolio
- RISCCLargest single grant (EUR 1.19M) — risk-based cervical cancer screening with predictive modelling and digital applications, representing their highest-funded and most applied project.
- HEAPHuman Exposome Assessment Platform integrating wearable sensors, AI, big data, and FAIR data principles — signals their move into digital health infrastructure.
- TO_AITIONTackles the under-researched cardiovascular-depression comorbidity through immune-metabolic biomarkers, an unusual cross-disciplinary angle for a public healthcare body.