Norwegian precision medicine SME building genetic and registry-based prediction tools for psychiatric disorders and cardiovascular comorbidities.
Precision Health AS is a Norwegian health technology SME that applies data science and predictive modelling to large-scale health data — national registries, biobanks, and eHealth records — to build clinical stratification and prediction tools. Their core expertise sits at the intersection of psychiatric medicine and genomics: they work on identifying genetic and lifestyle risk factors that predict disease onset, drug response, and adverse treatment outcomes across mental health conditions. In European consortia, they contribute specialist analytical and clinical data integration capabilities, particularly around real-world evidence from Scandinavian health infrastructure. Their work is directly relevant to personalizing treatment in psychiatry and understanding how comorbid physical conditions complicate mental health outcomes.
Both CoMorMent and REALMENT address mental health conditions — severe mental illness, schizophrenia, bipolar disorder, and major depressive disorder — using prediction and stratification methods.
Registries and biobanks appear in both projects; REALMENT explicitly combines eHealth records with biobank and national registry data in a big-data integration framework.
REALMENT focuses on psychopharmacology outcomes — drug response, adverse effects, and genotype-based prediction — signalling growing expertise in precision psychiatry drug profiling.
CoMorMent is specifically designed to predict comorbid cardiovascular disease in individuals with mental disorders, requiring cross-disease computational modelling.
Genetic risk appears in CoMorMent's cardiovascular comorbidity work and re-emerges in REALMENT through genotype-based drug response profiling.
Their first project (CoMorMent, 2020) centred on the physical-mental health interface — predicting cardiovascular risk in people with severe mental illness, drawing on biobanks, registries, and lifestyle data. The second project (REALMENT, 2021) pivoted deeper into pure psychiatric territory: schizophrenia, bipolar disorder, and depression, with a strong new layer of pharmacogenomics — drug response, adverse effects, and genotype profiling. The trajectory is clear: from broad comorbidity risk prediction toward precision psychiatry, where treatment selection is guided by genetic and real-world clinical data.
They are moving toward genotype-informed psychiatric treatment personalisation — a high-growth area where drug selection and dosing are guided by individual genetic profiles and real-world outcome data.
Precision Health AS has participated exclusively as a consortium partner — never as a project coordinator — suggesting they operate as a focused specialist contributor rather than a project driver. Despite only two projects, they have accumulated 18 distinct partners across 11 countries, which indicates they joined well-connected, large RIA consortia rather than small bilateral collaborations. This pattern points to an organisation that is sought out for a specific technical contribution and integrates smoothly into diverse multinational teams.
With 18 unique partners across 11 countries from just two projects, their network footprint is disproportionately broad for their size — a sign they operate within large, internationally distributed health research consortia. Their Norwegian base likely gives them access to Scandinavian national health registry infrastructure, which is a valued asset in European precision medicine networks.
Precision Health AS occupies a narrow but increasingly valuable niche: a private-sector SME with direct access to Norwegian health registry and biobank infrastructure, positioned inside academic-led psychiatric research consortia. Unlike university groups, they bring commercial agility and a product-oriented mindset to data-heavy research projects. For consortium builders, they offer rare combination of real-world Scandinavian health data access, psychiatric clinical expertise, and computational prediction tool development — without the overhead of a large institution.
