LSE Principal Investigator: Elias Mossialos, Alistair McGuire, Alex Carter
Region: UK
Keywords: artificial intelligence, high blood pressure treatment, clinical decision support tool, patient data integration
An international research team has received a ten million euro grant from Horizon Europe and UK Research and Innovation. The HYPERMARKER team will develop and test tools supported by artificial intelligence that allow clinicians to select the best treatment for each individual patient with high blood pressure. The consortium comprises 12 partners, including world leaders in health data science, patient advocacy and industry.
Hypertension, or high blood pressure, is a severe medical condition and the single most significant contributor to circulatory disease. It continues to dominate globally as one of the leading causes of death and morbidity, with a high social and economic burden on patients and health care systems. Whilst many treatments for hypertension are available, control of blood pressure remains poor in most countries, with avoidable consequences such as heart attacks, strokes, kidney disease and dementia.
The best treatment for each patient
The HYPERMARKER research team is developing a clinical decision support tool that will allow clinicians to make an informed selection of antihypertensive medication for each individual patient. "We are developing usable prediction algorithms that can help clinicians in deciding what the right hypertension treatment is for the right patient," explains project lead Professor Grobbee at UMC Utrecht. By measuring and analysing small molecules in the blood that interact with body systems, the response to medications can be predicted. “Putting together a ‘pharmacometabolic’ profile has the potential for a step-change in how we treat many diseases”, says project co-lead Professor Hankemeier from Leiden University.
Developing a usable tool
In HYPERMARKER, patient cohorts from eleven European countries will provide data to develop the clinical decision support tool. Artificial intelligence approaches will be used to integrate this information with clinical factors, using deep learning methods to isolate what is most important to determining treatment for each patient. The tools will be validated and refined through an innovative randomised clinical trial across four countries supported by patient and public engagement. “Where HYPERMARKER stands apart is robust evaluation and iteration to achieve an implementable tool with a roadmap for regulatory approval. We aim to make a real difference in daily practice and help to improve patient care”, explains project co-lead Professor Kotecha from the University of Birmingham.