By a novel combination of world-class exercise-, hypertension-, mathematical modelling-, machine learning-, statistical-, biosensor-, genetic epidemiology- and population-based research we will develop a personalized Medical Digital Twin (MyMDT) that serve as a transformative platform for patient specific hypertensive intervention. MyMDT shall identify, and implement, primary and secondary hypertension prevention schemes to improve individual health outcomes and reduce health care cost. MyMDT will radically improve prevention and treatment of hypertension and bring NTNU to the international forefront of translational hypertension research.

A rapidly ageing population brings challenges to public health systems due to a massive demand for health care services by patients with age/lifestyle-related disorders. Therefore, the World Health Organization (WHO) and EU health care’s systems calls for novel solutions that facilitate monitoring of own health that guide actions to promote healthy and active ageing. Essential hypertension is one of the most common age- and life-style related chronic disorders affecting more than one billion people worldwide. WHO1 considers hypertension to be by far the most important source of morbidity and mortality. By disposing for heart failure, kidney disease, stroke, and dementia and the subsequent costs to society, hypertension is a major therapeutic target for improved health and wellbeing worldwide. Previous physiological model studies have identified arterial compliance as a key explanatory factor for primary hypertension, and that normally functioning kidneys cannot restore blood pressure to normal levels in patients with arterial stiffening. Further, physical activity (PA) has been shown to have a positive effect on arterial compliance and thereby hypertension3. However, to our knowledge no causally cohesive personalized medicine models for hypertension have taken effects of PA into account and made it available in a clinical decision support system (DSS). MyMDT will develop a platform tailored for patient specific hypertension diagnostic, prognostic and treatment. To realize this ambition, we bring together world class competences on exercise physiology (CERG), cardiovascular modeling, machine learning (ML), statistics, and biobanks and health studies (HUNT). Clearly MyMDT is a truly multi-faculty, multi-disciplinary personalized medicine initiative.

In this dynamic setting we will develop MyMDT, which will be a “living” digital model that integrate physiological simulation and ML with data streams from sensors/wearables, in order to reflect changes of its real-life twin, the patient. MyMDT will be a patientspecific and time evolving version of the Medical Digital Prototype (MDP), which in turn is a generic model that integrates population-based data via ML.