Imagine if your doctor knew exactly which blood pressure pill would work for you without any trial and error. Instead of guessing, they use a blood test and a smart computer program to see how your body processes medicine. It's like having a personalized map that leads straight to the right treatment.
Hypertension is a leading cause of death and accounts for 10% of healthcare costs, yet treatment is often a trial-and-error process. This leads to uncontrolled blood pressure and increased cardiovascular morbidity.
A pharmacometabolomics platform and AI-driven predictive models. These are being integrated into a clinical decision support tool to guide drug selection.
If you are a drug developer dealing with high patient dropout rates in clinical trials — this project developed predictive models that identify which patients will respond to specific drug classes. This allows for better patient stratification and higher success rates in trials.
If you are a diagnostic company dealing with a lack of precision tools for cardiology — this project developed a pharmacometabolomics platform that identifies biomarkers for treatment response. This can be turned into a commercial test to guide physician prescriptions.
If you are a software provider dealing with generic medical guidelines that don't account for individual patient chemistry — this project developed a clinical decision support tool. This tool helps doctors choose between angiotensin inhibition, calcium antagonists, or beta-blockers based on evidence.
Based on available project data, the specific commercial price of the tool is not mentioned; however, the project received an EU contribution of EUR 8,046,250 for development.
The project is currently in the development and validation phase, utilizing cohorts from 11 European countries and planning an RCT across 4 sites to refine the tool before routine care uptake.
Based on available project data, specific licensing terms are not provided, but the project emphasizes FAIR data principles to ensure findings are accessible and applicable.
The project period runs from 2023-01-01 to 2026-12-31, suggesting the tool will be refined and validated by the end of 2026.
The project is building a clinical decision support tool and a framework for uptake in routine care to ensure it fits into standard medical practice.
The consortium is well-balanced for commercialization, featuring a 31% industry ratio with 4 industrial partners, including 3 SMEs. With 13 partners across 5 countries, the group combines academic research (6 universities, 2 research institutes) with practical industrial application, increasing the likelihood of a successful market transition.
Contact the Universitaire Medisch Centrum Utrecht for partnership inquiries.
Contact us to explore licensing opportunities for the pharmacometabolomics platform.
