ABOUT
AI MULTIPLY.
We are dedicated to advancing healthcare through innovative research and cutting-edge AI technology. Our goal is to unravel the complexities of pharmacy and disease clustering across life-course.
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).
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What our research is about?
Our ultimate aim is to develop new AI techniques that will help doctors to provide more personalised, effective, and equitable healthcare for people with multiple long-term health conditions.
This involves research using various patient-derived databases to accomplish the following goals:
* Figure out how different long-term health conditions develop and interact over time
* Identify critical moments or “tipping points” where health conditions start to rapidly progress
* Create ways to predict and potentially prevent sudden worsening of health
* Understand how factors like ethnicity, social status, and gender impact health outcomes
* Discover why some groups of people experience worse health trajectories
* Help to develop strategies to reduce these health disparities
* Define what makes medication use “appropriate” or “inappropriate” for people with multiple health conditions
* Create proof of concept tools that can help doctors make better decisions about prescribing medications
* Conduct trials with patient-derived data to explore the possibilities of safely reducing unnecessary medication use
* Create AI-powered proof of concept clinical decision support tools that can help healthcare professionals to more quickly identify patients at high risk of health complications
* Make these AI tools transparent and explainable, so doctors understand how recommendations are generated
* Involve patients directly in designing and guiding the research
* Ensure research questions and solutions reflect real patient experiences and needs
* Build trust and understanding between researchers and communities
WHO WE ARE
The AI MULTIPLY consortium brings together researchers across a number of universities, the NHS and Social Action for Health.
We are a Research Collaborative which has been awarded funding from the National Institute for Health and Care Research (NIHR) to investigate the use of artificial intelligence for multimorbidity and polypharmacy.
OUR PARTNERS
We are strengthened by partnerships with leading institutions dedicated to advancing healthcare research and innovation.
AI MULTIPLY brings together researchers from a number of organisations including:
(Click links below to find out more)
Bradford Teaching Hospitals NHS Foundation Trust (BTHFT)
Cumbria, Northumberland, Tyne & Wear NHS Foundation Trust (CNTW)
The University of Edinburgh (UoE)
Newcastle upon Tyne Hospitals NHS Foundation Trust (NUTH)
Queen Mary University London (QMUL)
Social Action for Health (SAfH)
Our VISION AND AIMS
Using artificial intelligence (AI) to characterise the dynamic inter-relationships between polypharmacy and multiple long-term conditions across diverse UK populations and inform health care pathways.
People who live with a number of medical conditions (multiple long-term conditions or MLTCs) are at high risk of poor health. They are often prescribed multiple medicines. When the number of medicines is greater than five, this is called polypharmacy. The relationship between MLTCs and polypharmacy is complex and not well understood.
We know that some patients enter a downward spiral, developing an increasing number of conditions and being prescribed more and more medicines.
This can cause health problems, as individual medicines may interact with one another or have side-effects. Other medicines may modify the downward spiral by preventing the development of conditions such as heart disease and cancer. All of this makes it difficult to design interventions to ensure medicines are prescribed in combinations that do more good than harm.
Our long-term goal is to better understand the dynamic relationship between MLTCs and polypharmacy, to optimise the medicines prescribed for individual patients. This research will also identify key points for intervention, to maintain the best possible health trajectory for people with MLTCs.
Our team
Our group is made up of experts across a range of fields: from research specialists who are experts in the data science field to clinicians with years of experience treating patients. Regardless of their background, each member of the consortium is dedicated to using AI and machine learning to develop strategies for prevention and improved management of multiple long term conditions.
Work package 1 & 2
DATA ACCESS, DATA WRANGLING, DATA ENGINEERING/
AI FOR MLTC AND POLYPHARMACY CLUSTERS, TIME COURSE AND TRAJECTORIES
Professor Michael R Barnes – Work Package Lead
Professor of Bioinformatics and Director of the Centre for Translational Bioinformatics (Queen Mary’s University London)
Work package 3
TOWARDS INTERPRETATION AND CLINICAL DECISION MAKING
Dr Dexter Canoy – Work Package Lead
Senior Lecturer in Epidemiology and Public Health (Newcastle University)
Professor Barbara Hanratty – Work Package Lead
Professor of Primary Care and Public Health (Newcastle University)
Dr Soraia Sousa – Work Package Lead
Mental Health Lead. Honorary Clinical Senior Lecturer (Newcastle University)
Work package 4
SOCIAL SCIENCE INVESTIGATION OF INTERDISCIPLINARY ENTANGLEMENTS
Work package 5
HEALTH AND SOCIAL CARE OUTCOMES: TRANSLATION INTO PRACTICE
Cross-Cutting
INEQUALITIES
Cross-Cutting
PATIENT AND PUBLIC INVOLVEMENT AND ENGAGEMENT
NEWS & EVENTS
Stay updated with the latest
developments from AI MULTIPLY.