The Alan Turing Institute, in conjunction with Swansea University and the University of Edinburgh, is developing data standards, disseminating best practices, and building community around researchers, patients and the public involved in AI for multiple long-term conditions research.
The innovative Research Support Facility is part of a £23 million investment by the NIHR in AI, and will connect researchers across the consortia, to ensure the investment delivers long-term, real-world impact for the programme and beyond.
Explaining the science
The new Research Support Facility (RSF), based at the Turing in conjunction with Swansea University and University of Edinburgh, will offer AI and advanced data science support to the research teams funded by AIM and foster collaboration. The facility, led by Dr Kirstie Whitaker and Professor Chris Holmes, will embed best practices in data security and standards, reproducibility, and public and patient engagement across the research collaborations funded by the programme, ensuring effective knowledge sharing and reinforcing the Turing’s role as a national convenor and capacity builder in data science and artificial intelligence.
The Research Support Facility work is split across five, interconnected themes:
Theme 1: Reproducible, secure and interoperable infrastructure
This theme will bring different research collaborations across the UK together within a trusted research environment to
Theme 2: Accessible, research ready data
Data wranglers, experts in data curation and quality control, will work with the Research Collaborations to align
Theme 3: Community building and training
This theme aims to build connections between early career researchers across the AIM programme so their existing
Theme 4: Patient and public involvement and engagement
Enhancing existing patient and public involvement networks across the AIM programme, this theme will support and
Theme 5: Sustainability and legacy
This theme will work with researchers to embed outputs in existing communities, both clinical and academic, and
An estimated 14 million people in England are living with two or more long-term conditions, with two-thirds of adults
People who develop multiple long-term conditions (MLTC) often do not have a random assortment of diseases but rather a largely predictable cluster of conditions. Developing a better understanding of these disease clusters, including how they develop over the course of a person’s life and are influenced by wider determinants of health, requires novel research and analytical tools that can operate across complex datasets.
The Artificial Intelligence for Multiple Long-Term Conditions (AIM) call, from the National Institute for Health and Care Research (NIHR), in partnership with NHSX, 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 life course.
To support this work, the AIM RSF will host a series of ‘open invitation talks’ from thought-leaders and experts on aspects of data science and MLTC research. The talks will be open to everyone across the AIM programme and the broader multiple long-term conditions research community. Sessions will be made available on YouTube afterwards.
The series is scheduled for the second week of each month on Tuesdays at 1:30-2:30, starting on 8th March 2022.
For more information about the RSF’s programme of events, and to register for future sessions, please go to this page.
The NIHR (National Institute for Health and Care Research) has awarded almost £12 million to new research that will use advanced data science and AI methods to identify and understand clusters of multiple long-term conditions and develop ways to prevent and treat them. The Alan Turing Institute, alongside Swansea University, University of Edinburgh and MRC Harwell, has been awarded £3 million to establish a new Research Support Facility as part of the programme. Find out more.