In this project, we will evaluate the use and performance of a CE-marked device (wearable), which uses sensors to measure breathing rate, pulse rate, skin temperature, and heart rate variability for the purpose of early detection and monitoring of COVID-19 in general and high-risk populations. At the same time, a mobile application will be used to track participant-reported symptoms. A prospective, observational study will follow 13,000 individuals from the general population and 7,000 high-risk individuals wearing the device and responding to participant self-report parameters via a purpose-designed app. Based on this data, an algorithm will indicate which individuals likely require general practitioner (GP) care (for COVID-19 diagnostic testing, further vital signs assessment, and/or treatment) and/or hospital care. To evaluate algorithm performance, the cohort will be tested for COVID-19 antibodies at the end of follow-up. COVID-19 seropositivity in the intervention cohort will be compared seropositivity in a control population of 20,000 individuals drawn from the same populations using the application only. Thus, this project will deliver a large body of information on COVID-19 PCR testing and antibodies that can be used to develop additional diagnostics and therapeutics in addition to validating remote vital signs and self-reported symptoms monitoring systems.

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 cohorts from 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.