AI-powered personalised medicine tool for hypertension being developed

Hypertension patients could receive a personalised medication profile thanks to a new, artificial intelligence-supported research project.

An international research team has received a ten million euro grant from Horizon Europe and UK Research and Innovation to develop and test tools that incorporate artificial intelligence-based machine learning platforms, that allow clinicians to select the best treatment for each individual patient with high blood pressure.

The HYPERMARKER consortium consists of 12 partners, including the Institute of Cardiovascular Sciences (ICVS) and the Institute of Cancer and Genomic Sciences at the University of Birmingham, made up of world leaders in health data science, patient advocacy and industry.

Researchers from the University of Birmingham will be leading the data analysis of patient cohorts from eleven European countries 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. Led by ICVS, the tools will be validated and refined through an innovative randomised clinical trial across 4 countries including recruiting patients from University Hospitals Birmingham.

Professor Dipak Kotecha, Professor of Cardiology and Cardiac Imaging at the Institute of Cardiovascular Sciences at the University of Birmingham and project co-lead said:

“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”.

Professor George Gkoutos, Chair of Clinical Bioinformatics at the Institute of Cancer and Genomic Science , Associate Director of Health Data Research UK and project co-lead observed:

“HYPERMARKER will employ state of the art AI-based multimodal multiomics integrative approaches to leverage the use of pharmacometabolomics and derive a personalised treatment approach based on the respective patient’s metabolomic profile and improve outcomes for patients with hypertension”

Tailoring the treatment to each patient
The HYPERMARKER research team is developing a clinical decision support tool that will allow clinicians to make an informed selection of the most suitable antihypertensive medication for each individual patient, with the least side effects.

Professor Grobbee at UMC Utrecht who is leading the project said:

“We are developing usable prediction algorithms that can help clinicians in deciding what the right hypertension treatment is for the right patient.”

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