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The University of Southampton
Turing @ Southampton

A Smart Algorithm for Optimising Hypertension Management Strategies

Overview

This research project aspires to create a cutting edge smart algorithm in the burgeoning area of Big Data science. This is a field in which The Alan Turing Institute (ATI), the University of Southampton, and private companies are heavily investing, with the aim of producing real-world impact at the largest scales from medicine to banking. For example, STFC have funded a Doctoral Training Centre in Data Intensive Science (DISCnet), and one of the Astronomy students (Lorenzo Zanisi) was able to spend some time on secondment at St Thomas’ Hospital. This secondment laid the foundation for an advantageous interdisciplinary collaboration between the astronomical and medical communities that promises a leap forward in our understanding, treatment and subsequent savings in healthcare procedures. Current medical management of many common conditions in fact involves initiating or changing treatment based on quantitative, semi-quantitative or qualitative thresholds.

This project proposes an innovative multi-disciplinary science programme aimed at developing optimal blood pressure (BP) management strategies for given measurement uncertainties. Building on a promising emergent collaboration between the Astronomy group at the University of Southampton and the Department of Clinical Pharmacology of St Thomas' Hospital, we will generate a cutting-edge Hierarchical Bayesian Monte Carlo model that can probe the complex behaviours of large groups of patients, by effectively combining skills and expertise in statistical physics and computational science, with clinical management of BP. Our project has the following objectives:

  1. To build a platform to reflect real-world management of BP.
  2. To use the new platform to conduct 'in silico' clinical trials that explore the efficiency of various management strategies.
  3. To apply for further funding, within the PPAN/UKRI remit but also targetting additional funding streams, such as the Wellcome Trust or the British Hearth Foundation, to perform clinical trials based on the most promising in silico results.

Investigators

Principal Investigator: Dr Francesco Shankar

Co-Investigators: Professor Philip Chowienczyk and Dr Christopher Floyd (St Thomas' Hospital, King's College, London) and Dr Mat Smith and Mr Lorenzo Zanisi (Southampton)

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