Queen Mary University launch new remote monitoring app project

Researchers from Queen Mary University of London are launching a new project with healthtech startup Living With, aiming to revolutionise the treatment of Rheumatoid Arthritis.

The project will develop an AI driven product to help to optimise treatment of Rheumatoid Arthritis patients, based on health data they have submitted via Living With’s remote monitoring app.
The AI model developed uses patient data with expert knowledge to automatically monitor changes in a patient’s condition. It is hoped the approach could support clinicians to make treatment decisions, for example whether they can safely reduce the dose of biological medicines, which could open up access to these treatments for a wider number of patients. Dose tapering, where a patient’s medication is gradually reduced, has been suggested as a way to allow more patients to access these treatments.
The programme is being funded as part of the EPSRC funded project PAMBAYESIAN and has received additional support of £50,000 from the Queen Mary University Enterprise Zone (QME)Pump Priming award. This funding will enable Living With to integrate an online prototype of the new model onto their existing platform that is already used by a number of NHS trusts.
Chris Robson, CEO at Living With, said: “We’re excited to work with the Queen Mary PAMBAYESIAN team to prototype an AI driven product for RA patient biologic optimisation, combining our remote management product with their Bayesian network methodology.”
“This award enables us to formalise our existing partnership with Queen Mary and work together to develop intelligent biologic therapy optimisation, which could enable these drugs to be prescribed to a much wider number of RA patients.”
Professor Norman Fenton, Professor of Risk Information Management at Queen Mary, said: “By combining Living With’s existing RA product with our Bayesian Network Model doctors will be able to monitor changes in a patient’s condition, and predict future responses, based on simple regular inputs.”
“This will provide confidence to doctors making key decisions about reducing the amount of biological medicines patients receive. Getting these decisions right would benefit both patients and the NHS, and potentially save millions of pounds every year as the typical cost per patient is around £1500 per month.”

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