Published: 01 September 2022
The NIHR has awarded over £10 million of funding to four collaborative projects that will use artificial intelligence (AI) methods to better understand clusters of multiple long-term conditions.
This second round of funding brings the total awarded for research and to the innovative new Research Support Facility to £23 million.
The new Research Collaborations will look at improving treatment for people who are prescribed several different medicines together, why some people develop multiple conditions early in life, and which conditions are more likely to occur together in people with intellectual disabilities.
The research has been funded through the Artificial Intelligence for Multiple Long-Term Conditions (AIM) call. This call funds research that combines data science and AI methods with health, care and social science expertise to identify new clusters of disease and understand how multiple long-term conditions develop over the course of people’s lives.
In September 2021 the AIM call funded three Research Collaborations, nine smaller Development Awards to allow the researchers to work up their ideas, and a Research Support Facility that provides AI and advanced data science support to the funded research teams and fosters collaboration.
Professor Lucy Chappell, Chief Executive of the NIHR, said: “Through the AIM call, NIHR has funded over £20m of ground-breaking research and an innovative Research Support Facility. This research is critically important to understand how conditions cluster together, which will, ultimately, help improve the lives of the estimated 14 million people in England living with multiple long-term conditions.”
Four new innovative projects
Treating multiple long-term conditions is a balancing act. People are often prescribed many different medicines together (known as polypharmacy). Sometimes these medicines and their side effects can interact in unexpected ways, causing further problems.
The AI-MULTIPLY study (Using AI to characterise the dynamic inter-relationships between MUltiple Long-term condiTIons and PoLYpharmacy), led by Professor Nick Reynolds, University of Newcastle upon Tyne and Professor Michael Barnes, Queen Mary University of London, is using AI to better understand the relationships between multiple long-term conditions, polypharmacy, and personal and social factors, to optimise treatment for individual patients.
The DynAIRx study (AI for dynamic prescribing optimisation and care integration in multimorbidity) led by Professor Iain Buchan, University of Liverpool and Dr Lauren Walker, Royal Liverpool University Hospital, is also examining the issue of polypharmacy. This project aims to develop easy to use AI tools that support GPs and pharmacists to find patients with multiple long-term conditions who might be offered a better combination of medicines.
The MELD-B study (Multidisciplinary Ecosystem to study Lifecourse Determinants and Prevention of Early-onset Burdensome Multimorbidity), led by Dr Simon Fraser and Dr Nisreen Alwan, University of Southampton, will identify why some people develop multiple long-term conditions early in their lives and the impact this has on them. This will help find key time points when prevention efforts should be targeted or strengthened to reduce a person’s risk of developing clusters of conditions, focusing on those that are most ‘burdensome’.
The DECODE study (Data-driven machinE-learning aided stratification and management of multiple long-term COnditions in adults with intellectual disabilitiEs), led by Dr Gyuchan Thomas Jun, Loughborough University and Dr Satheesh Gangadharan, Leicestershire Partnership NHS Trust, will use machine learning to find out more about multiple long-term conditions in people with intellectual disabilities. The results will help develop a new joined-up model of care for this diverse population group, two-thirds of whom have two or more long-term health problems.
Generating a research pipeline
Three of the four newly announced Research Collaborations had previously received a smaller nine-month preparatory Development Award. NIHR funded nine Development Awards through the AIM programme last year.
Development Awards have proved to be a successful way of creating a pipeline of research and building capacity and capability across multidisciplinary teams around AI in multiple long-term conditions. They have allowed researchers to establish new collaborative partnerships, acquire and bring together data, and develop and test AI methodologies to identify clusters of multiple long-term conditions.
- Using artificial intelligence (AI) to characterise the dynamic inter-relationships between MUltiple Long-term condiTIons and PoLYpharmacy and across diverse UK populations and inform health care pathways (AI-MULTIPLY)
- Multidisciplinary Ecosystem to study Lifecourse Determinants and Prevention of Early-onset Burdensome Multimorbidity (MELD-B)
- DynAIRx: AIs for dynamic prescribing optimisation and care integration in multimorbidity
- DECODE: Data-driven machinE-learning aided stratification and management of multiple long-term COnditions in adults with intellectual disabilitiEs