Queen Mary University of London

ID-538

This study will validate and refine a machine-learning model using diverse NCL primary care data to predict blood pressure response to treatment, supporting personalised hypertension management and future clinical decision-support tools

The project is a research collaboration between QMUL clinicians, data scientists and machine learning experts, and Barnet PCRU – that allows cutting edge scientific research and knowledge exchange to take place between academic and community settings. The project is already engaging future primary users (GPs, nurses and pharmacists) who will apply project outputs to tailor BP management, and is expected to lead to high impact academic publications for the wider scientific and clinical community. The immediate objective is to validate ML BP prediction model using anonymised UK primarycare data, generating robust evidence of real-world accuracy, fairness, and generalisability. Completion of this step will de-risk the technology technically and clinically, producing a development-ready asset for next-stage funding and partnerships. The project lays the groundwork for large-scale grant applications and clinical testing in partnership with GP colleagues which, if successful, would enable commercialisation as a standalone app or integration into existing healthcare platforms. The collaboration is being highlighted in the NIHR Barts BRC renewal application to further the currently funded hypertension workstream as a partnership that will facilitate translation of research in community settings.

20/08/2026

28/02/2027

21/08/2026

De-Personalised

24/08/2026

TRE