Doctors currently prescribe blood pressure drugs largely by trial and error, cycling through different medications until one works. HYPERMARKER aims to replace that guesswork with a blood test that predicts which drug will work for a given patient before they take it. High blood pressure is the leading cause of heart disease and stroke across Europe, accounting for nearly 10 percent of all healthcare costs. The problem is that five major classes of blood pressure drugs exist—angiotensin inhibitors, calcium antagonists, beta-blockers, and others—and no reliable way to tell which one a patient will respond to. Patients often spend months on ineffective treatments, experiencing side effects and delays in blood pressure control. The project will analyse metabolomic profiles—chemical fingerprints in the blood—from thousands of patients across eleven European countries. Using AI and deep learning, the team will build prediction models for individual drug responses, then validate them in a clinical trial across four European sites. The end product is a clinical decision support tool that tells a clinician: this patient will respond best to drug A, not drug B or C. If successful, the tool could be integrated into routine care across Europe, cutting the time to effective treatment, reducing side effects, and lowering the healthcare burden of uncontrolled hypertension.
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Hypertension, or high blood pressure (BP), is a serious medical condition, and the single biggest contributor to circulatory diseases which continue to dominate as the leading cause of death and morbidity across the EU. It accounts for almost 10 percent of all healthcare-related costs. Systolic hypertension leads to a broad variety of diseases with an immense impact on both patients and healthcare systems. HYPERMARKER will unleash the potential of pharmacometabolomics to provide a ‘smart’ prescription of antihypertensive therapy. Well-phenotyped cohortsfrom eleven European countries will provide metabolomic profiles and blood samples for pharmacometabolomic assessments to identify predictors of treatment response in hypertension using advanced AI and deep learning methods. Prediction models for individual treatment responses to antihypertensive medication will be clinically validated and refined through an innovative RCT across 4 sites in Europe. The result is a clinical decision support tool that will give clinicians the ability to make an informed selection of whether the patient they are treating will best respond to the use of angiotensin inhibition, calcium antagonists, beta-blockers, or a range of other existing drugs with evidence-based for BP control. To ensure sustainability, the project will also develop a framework for the uptake of this tool in routine care for patients with hypertension across Europe and beyond. HYPERMARKER will be implemented by a group of world-class scientists and clinicians from a diversity of disciplines who have collaborated multiple times and have a track record of leading key national and EU-funded initiatives to deliver high-impact results.
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