Queen Mary partner with healthtech startup Living With to help Rheumatoid Arthritis patients
16 November 2020
Working with innovative healthtech startup Living With, researchers from Queen Mary University of London are launching a new project that could revolutionize the treatment of Rheumatoid Arthritis (RA) and save the NHS millions every year.
The project will develop an Artificial Intelligence driven product to help clinicians optimise treatment of RA patients based on health data they have submitted via Living With's remote monitoring app.
Researchers at Queen Mary, led by Professor Norman Fenton, Professor of Risk Information and Management and Queen Mary Turing Fellow, have developed a type of model, known as a Bayesian Network model, that combines real patient data with expert knowledge to automatically monitor changes in a patient's condition.
It is hoped this innovative approach could support clinicians to make important treatment decisions, for example whether they can safely reduce the dose of expensive biological medicines, which could open up access to these treatments for a wider number of patients.
The research forms 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.
Currently RA affects around 400,000 people in the UK. Medicines used to treat RA patients can be divided into two types, disease-modifying anti-rheumatic drugs (DMARDs) and biological therapies. Biological therapies are expensive and as a result primarily reserved for RA patients who have not responded well to other treatments.
Dose tapering, whereby a patient's medication is gradually reduced, has been suggested as a way to ease the economic burden of biological therapies and allow more patients to access these treatments. Whilst multiple studies suggest dose tapering is safe, to date this has not been performed at scale and the process requires frequent and time-consuming monitoring of patient measures by doctors.
Through this innovative project, the researchers will integrate AI with Living With's remote monitoring app to provide an efficient and intelligent system for optimising biological therapies for RA patients.
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 optimization, 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 School of Electronic Engineering and Computer Science, 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."
Updated by: Michal Filus