On Thursday February 29, 2024, 11:30-1:30pm ET leaders from the NIHR AIM Programme will present to the NIH Bridge2AI Consortium. The webinar will introduce the AIM Program goals and components associated with the People, Ethics and Data pillars of Bridge2AI.
Background on NIHR's AIM Programme
The NIHR has awarded £23 million to new research that will use advanced data science and artificial intelligence (AI) methods to identify and understand clusters of multiple long-term conditions (MLTCs) and develop ways to prevent and treat them.
The awards have been funded under the Artificial Intelligence for Multiple Long-Term Conditions (AIM) Programme over 2 waves of funding. The first wave has invested nearly £12 million into three Research Collaborations, nine Development Awards and a Research Support Facility. The second wave has invested around £10 million in four additional Research Collaborations, primarily stemming from previously funded Development Awards.
Wave 1 Awards:
- OPTIMising therapies, discovering therapeutic targets and AI assisted clinical management for patients Living with complex multimorbidity (OPTIMAL study)
- The development and validation of population clusters for integrating health and social care: A mixed-methods study on Multiple Long-Term Conditions
- Artificial Intelligence and Multimorbidity: Clustering in Individuals, Space and Clinical Context (AIM-CISC)
Wave 2 Awards:
- Using artificial intelligence (AI) to characterize 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)
- DECODE: Data-driven machinE-learning aided stratification and management of multiple long-term COnditions in adults with intellectual disabilitiEs
Other NIHR investments stemming from AIM Programme Development Awards:
- Inflammation, nutrition, and the evolution of multiple long term conditions – an AI-based analysis of intersectionality in longitudinal health data (the InflAIM project)
- Slide 16 outlines some early thoughts from NIHR AIM award holders with regards to opportunities for collaborations.
- Slide 17 introduces other investments the NIHR has made on AI, particularly in the context of our Invention for Innovation Programme.
- Slide 18 outlines specific challenge areas (e.g. cancer, mental health, respiratory), where the NIHR has made significant investments and that could offer exciting opportunities for AI applications. We are keen to explore synergies in those areas.
Activities of the AIM Consortium
Artificial Intelligence for Multiple Long-term conditions (AIM): A consensus statement from the NIHR AIM consortia