Artificial Intelligence for Multiple Long-Term Conditions (AIM)
- Research Specification for Research Collaboration and Development Awards
- Specific Guidance for Applicants (Research Collaborations ONLY)
- TEMPLATE Research Collaborations Stage 1 Application Form (you will be required to submit using an online application form on the Research Management System)
- Specific Guidance for Applicants (Development Awards ONLY)
- TEMPLATE Development Awards Stage 1 Application Form (you will be required to submit using an online application form on the Research Management System)
- Frequently Asked Questions (Research Collaboration and Development Awards ONLY)
- AiM Research Support Facility Research Specification
- AiM Research Support Facility Stage 1 Guidance for Applicants
- AiM Research Support Facility Stage 1 TEMPLATE application Form (you will be required to submit using an online application form on the Research Management System)
- Frequently Asked Questions (Research Support Facility ONLY)
The NIHR invites proposals to undertake programmes of research to spearhead the use of artificial intelligence (AI) methods to develop insights for the identification and subsequent prevention of multiple long-term conditions (multimorbidity) or MLTC-M.
Research funded through this initiative will use AI and data science methods, combined with expertise in clinical practice, applied health and care research and social science, to systematically identify or explore clusters of disease. In addition to the identification and mapping of new clusters of disease, the call seeks research to better understand the trajectories of patients with MLTC-M over time and throughout the life course, including the influence of wider determinants such as environmental, behavioural and psychosocial factors.
This competition aims to bring together multi-disciplinary Research Collaborations to build on our existing understanding of disease clusters in people with MLTC-M using ground-breaking AI techniques; and to grow capability for multi-disciplinary working in this crucial research area.
In order to facilitate new collaborations and build capability, this call has a two-stream approach.
• Research Collaboration - existing groups can apply for full Research Collaboration funding, building on their strong base of multi-disciplinary researchers and bringing on board new disciplines to meet the remit of the call, as required. Awards of £2.5-5m will be available for up to 36 months for a full Research Collaboration in wave 1.
• Development Award - applicants who are interested in applying but need more time and resources to develop a competitive proposal, may apply for a preparatory Development Award of up to £120k for 8 months before applying for a full Research Collaboration of £2.5-4m over up to 30 months at wave 2. Development Award holders will submit their full Research Collaboration application to the Wave 2 call.
We reserve the right to open the Wave 2 call to new Research Collaboration applicants. This decision will be made after the funders have reviewed the responses and funding awards made at Wave 1.
In addition, NIHR invites proposals for a Research Support Facility (RSF) to work with Research Collaborations funded through the NIHR Artificial Intelligence for Multiple Long-term Conditions (AIM) call. Up to £3m funding is available for up to 40 months to support the Research Collaborations funded through this call. The RSF will focus on the delivery of centralised AI and advanced data science support; capacity and capability in AI and MLTC-M research; foster a collaborative approach and a culture of shared learning; and provide a leadership role to facilitate impact from the AIM call.
Please be advised that the Research Collaboration and Research Support Facility applications are a two stage process. The Development Award is a Single Stage (full) Application Process.
The deadline for submissions is 29 September 2020 at 1pm.
General enquiries regarding the application and commissioning process can be directed to the AIM Team via the online form. Please ensure that you leave a contactable phone number and a member of the team will get back to you