Artificial intelligence funding
Artificial intelligence has enormous potential for improving healthcare across all areas of the NHS and social care. NIHR currently has three routes for researchers and industry partners seeking funding for health research involving artificial intelligence.
The NIHR has three funding streams to support health and care research that involves artificial intelligence (AI).
The Artificial Intelligence in Health and Care Award (AI Award) supports AI solutions across the whole development pathway, from initial feasibility to clinical implementation. It is funded by NHS England and NHS Improvement and the NIHR in partnership with the Accelerated Access Collaborative and NHS AI Lab. Read about projects funded in Competition 1, Competition 2 and Competition 3.
The Artificial Intelligence for Multiple Long-Term Conditions (Multimorbidity) call (AIM) supports research to spearhead the use of AI and data science to address the challenges of multiple long-term conditions (multimorbidity) or MLTC-M. The call is part of the NHS AI Lab and is enabled by the NIHR.
The Artificial Intelligence and Racial and Ethnic Inequalities in Health and Care call supports research to advance AI and data-driven technologies in health in ways that better meet the needs of minority ethnic populations. The call is jointly funded by NHS AI Lab and The Health Foundation and enabled by the NIHR.
Health and Care
The AI in Health and Care Award will accelerate the testing and evaluation of the most promising AI technologies that meet the strategic aims set out in the NHS Long Term Plan.
The AI in Health and Care Award is run in partnership with the Accelerated Access Collaborative (AAC) and NHS AI Lab.
The AI in Health and Care Award supports AI technologies across the spectrum of development, from initial feasibility to evaluation within clinical pathways in the NHS and social care settings, to the point that they could be nationally commissioned.
Phases and specifications
Competition 1 results were announced in September 2020. Competition 2 awarded projects were announced in June 2021. In 2022, Competition 3 invited applications to Phases 2-4 of the AI Award.
- Phase 2 is intended to develop and evaluate prototypes of demonstration units and generate early clinical safety and efficacy data.
- Phase 3 is intended to support first real-world testing in health and social care settings to develop further evidence of efficacy and preliminary proof of effectiveness, including evidence for routes to implementation to enable more rapid adoption.
- Phase 4 is intended to identify medium stage AI technologies that have market authorisation but insufficient evidence to merit large-scale commissioning or deployment. We are supporting testing and evaluation of these technologies within routine clinical or operational pathways to determine efficacy or accuracy, and clinical and economic impact.
Phase 2 and Phase 3 are delivered through the well-established and robust mechanisms underpinning the NIHR Invention for Innovation (i4i) programme and the NHS England and NHS Improvement SBRI Healthcare programme. The Phase 2 and Phase 3 awards are managed by the NIHR Innovations Programme Management Office, in close collaboration with the AAC Delivery Team.
Through Phase 4, the AAC Delivery Team facilitates systems adoption of the AI technologies into the NHS and/or social care settings.
Read more about the specifications for different phases in our guidance for applicants.
The Competition 3 launch webinar took place on Thursday 17 June 2021. This and previous webinars can be viewed on the NHS AI Lab Virtual Hub. Please note that you will need to request access to the hub by emailing email@example.com in order to view the webinars. The AI Lab Virtual Hub has been set up as a platform to allow stakeholders to directly connect rather than just coming through the award. We recommend that you join and you encourage collaborative partners to join for more resources and to engage with colleagues across the NHS.
Multiple Long-Term Conditions
The Artificial Intelligence for Multiple Long-Term Conditions (Multimorbidity) call (also referred to as the AIM programme) supports research to spearhead the use of advanced data science and AI methods - combined with existing methodology and expertise in clinical practice, applied health and care research and social science - to systematically identify new clusters of disease and the development of conditions over the life course. This research will develop insights into the identification and subsequent prevention of multiple long-term conditions (multimorbidity) or MLTC-M.
In 2020-2021 the £23m call generated a pipeline of data science and artificial intelligence translational research projects to understand and map clusters of MLTC-M. The call supported research collaborations and partnerships between leading academic institutions, health and care researchers, AI experts, and practitioners. This call aimed to grow capacity and capability for multi-disciplinary working in MLTC-M for the benefit of patients, practitioners and the public.
The call is part of the NHS AI Lab multimorbidity programme and is enabled by the NIHR.
NIHR has produced a Strategic Framework for MLTC-M research. This outlines what NIHR means when we talk about MLTC-M, our research priorities in this area and the actions we are putting in place to support them.
Read the NIHR Strategic Framework for MLCT-M research
What do we fund?
The AIM call funds programmes of research that 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.
The funding available through this call will lead to scientific understanding which will allow researchers to start addressing key challenges in the treatment and management of MLTC-M in the health and social care system in the future. We have three primary longer term aims that include:
- The development of solutions which will improve the quality of life and health outcomes for people with MLTC-M.
- The exploration of new approaches and future industry collaborations to diagnose disease early, progress drug development and address the burden of polypharmacy.
- The implementation of measures to reduce progression to a greater number of conditions.
In particular, we seek applications from cross-disciplinary and cross-institutional teams to develop research in this important field. A total of £23m was allocated between two streams - larger Research Collaborations and smaller, preparatory Development Awards.
Research Collaborations of £2.5-5m were funded for up to 36 months (in wave 1).
Applicants who were interested in applying for a Research Collaboration award, but needed more time and resources to develop a competitive proposal, applied for preparatory Development Awards of up to £120k for 8 months.
In addition, NIHR funded a Research Support Facility (RSF) to work with Research Collaborations funded through the AIM 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.
Read the call specification for full details of this funding call. Please note that at this moment, there are no further calls being planned for this initiative. This webpage is retained for information only.
Racial and Ethnic Inequalities
The AI and Racial and Ethnic Inequalities in Health and Care call funds research projects focused on enabling AI and data-driven technologies to deliver better health outcomes for minority ethnic communities.
This £1.55 million call will fund research to:
- Better understand and enable opportunities to use AI to ensure innovation happens in response to the health needs of minority ethnic groups
- Contribute to improving the quality, availability and appropriate use of datasets to account for ethnic diversity in the development of AI models
- Improve the development, testing and deployment of AI models across patient populations to reduce bias and improve the performance and accuracy of emerging and existing tools for different subpopulations
The call is jointly funded by NHS AI Lab and The Health Foundation and enabled by the NIHR. This call is a part of the NHS AI Lab’s AI Ethics Initiative, which will invest in research and trial practical interventions to ensure that AI products used in the NHS and care settings do not exacerbate health inequalities.
What do we fund?
The call will fund two categories of research:
1) Understanding and enabling the opportunities to use AI to address inequalities
- Funded by The Health Foundation
- Awards of £175,000 to £275,000
2) Optimising datasets, and improving AI development, testing and deployment
- Funded by the NHS AI Lab
- Awards of £200,000 to £500,000
Both categories will fund projects of 12 to 24 months duration.
The projects will be selected primarily on their potential value to the health service and social care system and on the improved outcomes delivered for those in receipt of care.
How do I apply?
This one stage funding call is open to UK-based higher education institutions, third sector organisations, charities, and NHS organisations or providers of NHS or social care services.
The call was open between 24 March and 28 April 2021.
A Q&A for potential applicants was held on Wednesday 10 March 2021 as part of the launch event for the NHS AI Lab AI Ethics Initiative. The recording of the event is available on NHS AI Virtual Hub (once registered). Another Q&A was held on Thursday 8 April.
The three AI calls are national competitions with applications reviewed by a national multi-disciplinary funding panel and assessor pool comprising specialist technical, clinical and commercial experts and patient and public representatives.
Expert assessors and panel members review all applications and make funding recommendations based on the quality of applications, with support from public and expert peer reviewers.
Members of NIHR Committees are required to declare any interests which conflict, or may be considered to conflict, with NIHR business, or may be perceived as influencing decisions made in the course of their work within NIHR programmes. All members are asked to complete the Register of Interest form (annually), which is intended to capture long term predictable interests that could be perceived to lead to conflicts of interest. These and other interests are judged on a case by case basis at individual meetings.
Our selection panels
View the full membership of the Artificial Intelligence in Health and Care Award panels.
View the full membership of the Artificial Intelligence and Racial and Ethnic Inequalities in Health and Care Panel.
We offer a wide variety of assistance during all stages of the application process. If in doubt, please get in touch. Our operating hours are 9am to 5pm.
AI in Health and Care Award
AI for Multiple Long-Term Conditions
AI and Racial and Ethnic Inequalities