This funding opportunity seeks to develop innovative AI research that can be applied to the most pressing health problems and change how health research is conducted. This programme will endeavour to bring together researchers from multidisciplinary and cross-sectoral teams in order to develop and progress a clear shared research agenda.
We aim to support projects that:
- will generate real world impact
- are co-created with stakeholders including but not limited to:
- AI experts
- health-related problem holders
- social scientists
- data owners
- end users
- relevant others (for example, the public, patients, and regulators)
Innovation in AI can tackle a range of health, social, scientific as well as technical issues. For example:
- use of AI within important or underexplored (from the perspective of AI) areas of health research, or both
- need for new or improved AI approaches and ways of applying AI in health research
- understanding and tackling pertinent data issues needed to progress health AI research
- ensuring AI is fit for use. Addressing issues of responsibility, bias, end user needs, and similar areas by incorporating these approaches, or redesigning existing tools taking into account responsibility, bias, end user needs to ensure they are fit-for-purpose
Projects are expected to:
- work across the nexus of the challenge spaces rather than solely within 1 area to ensure the benefits of this investment reaches as widely into the UK AI research and innovation landscape as possible
- comprise of cross-disciplinary teams with:
- technical knowledge of AI, data science and health and wellbeing
- those who understand how to develop projects that are trusted and responsible, particularly in respect of personal and protected data
- inclusion of experts on industry adoption and diffusion of innovation taken into consideration
- take into consideration how the AI tools developed will act as a platform for future applications in health research. For example underpinning future research, infrastructure, or informing wider health programmes or initiatives
You should focus on how the technology or methodologies will be developed. This may include (but is not restricted to):
- technical development
- broadening application from outside a new technology’s initial use to health research
- consideration of responsible AI approaches by design
You must identify a clear health challenge that will be tackled. There are a variety of ways in which AI can play an impactful role in relation to health but where barriers remain in enabling its full impact to be realised, including (but not limited to):
- the role of AI in integrating and understanding complex determinants of health. Examples include tackling inverse problems by integrating complex omics, healthcare, environment, lifestyle, biosocial and other datasets to generate novel insights. This could be applied to:
- address health inequalities
- establish biomarkers of health and predict resilience to health conditions across the lifespan
- develop in silico models for One Health to predict emergence of zoonotic diseases
- addressing limitations of AI in dealing with incomplete or small health datasets. Examples include:
- the potential strategies for synthetic data to complement ‘real world’ health data in clinical trials while maintaining public trust
- use of AI to parameterise interpretable models allowing mechanistic inference
- AI to uncover complex interactions within very large-scale fragmentary data such as those arising from microbiome research and rare disease research
- the role and acceptability of AI in decision making in health. Examples include:
- addressing potential biases, social and practitioner acceptance of use of AI in health
- embedding human attributes such as empathy, trust and responsible development of AI technologies
- novel approaches to experimentation. Examples include:
- automated and adaptive AI-guided research, whereby AI guides the discovery process through design, direction and analysis of high-throughput experiments, both open and closed loop. This could accelerate progress in areas such as fundamental discovery science (for example, functional genomics, anti-microbial resistance)
The programme is open across all areas that fall within UKRI health remit where the work:
- has the potential to contribute to improved human health, wellbeing or disease outcomes, including health-related discovery science
- makes a convincing case for being distinctive within the national landscape and addressing an unmet need
- involves substantive, and where appropriate innovative, AI approaches to tackling the challenge
- is cross-disciplinary or cross-sectoral and will benefit from the team-based approach
Attention should be paid to other major AI funding opportunities, in particular from UKRI, to avoid overlap which may reduce appetite for funding through this opportunity.
In addition, it is expected that each project will engage across their AI field as the landscape and a wider portfolio of investments supported by UKRI develops. It is expected that the successful projects will coordinate their activities to form a larger AI for health community network. The network will exchange ideas, challenges and solutions as well as act as a source of strategic intelligence for UKRI.
Leaders of each investment will be expected to represent this community in collaboration with other investments across UKRI.
A total of £13 million is available for spend. The maximum value for each award is £750,000.
The award duration will be 18 months. Grants must start latest by 1 October 2023 and must conclude on 31 March 2025. No additional spend can occur beyond this period.
Equipment over £10,000 in value (including VAT) and up to £400,000 is available through this funding opportunity. All equipment should be fully justified and essential to the mission of the investment. Smaller items of equipment (individually under £10,000) should be in the ‘Directly Incurred – Other Costs’ heading. It is expected the majority of the funding will go towards research activities.
This opportunity will follow the EPSRC approach to equipment funding.
Responsible innovation and trusted research
UKRI is fully committed to developing and promoting responsible innovation and trusted research. Research has the ability to not only produce understanding, knowledge and value, but also unintended consequences, questions, ethical dilemmas and, at times, unexpected social transformations.
We recognise that we have a duty of care to promote approaches to responsible innovation that will initiate ongoing reflection about the potential ethical and societal implications of the research that we sponsor. We encourage our research community to do likewise.
In common with other funding for AI across UKRI, this grant will be required to embed principles of responsible innovation and those of trusted research throughout their activities. You will be expected to engage with the relevant regulatory bodies where concerns may arise under the National Security and Investment Act. Aspects of bias, privacy, security and ethics should be considered where appropriate.
UKRI’s environmental sustainability strategy lays out our ambition to actively lead environmental sustainability across our sectors. This includes a vision to ensure that all major investment and funding decisions we make are directly informed by environmental sustainability, recognising environmental benefits as well as potential for environmental harm.
In alignment with this, UKRI is tackling the challenge of environmental sustainability through our ‘building a green future’ strategic theme. This aims to develop whole systems solutions to improve the health of our environment and deliver net zero, securing prosperity across the whole of the UK.
Environmental sustainability is a broad term but may include consideration of such broad areas as:
- reducing carbon emissions
- protecting and enhancing the natural environment and biodiversity
- waste or pollution elimination
- resource efficiency and a circular economy
UKRI expects its grants to embed careful consideration of environmental sustainability at all stages of the research and innovation process and throughout the lifetime of the grant.
You should ensure that environmental impact and mitigation of the proposed networking, research approaches and operations, as well as the associated project outputs, methodologies developed across science and engineering and outcomes is considered.
Furthermore, opportunities should be sought to influence others and leave a legacy of environmental sustainability within the broader operations of your academic and industry partners.
Equality, diversity and inclusion (EDI)
UKRI is committed to achieving equality of opportunity for all and aims to create an inclusive environment that encourages excellence in scientific research through good equalities practice.
Diversity is one of the core UKRI values, and we are working to ensure that the ways in which we fund embrace a diversity of:
- geographical locations
There has been a longstanding lack of diversity in the data science and AI sectors, particularly with regard to gender and ethnicity. We strongly encourage applications from under-represented groups.
Read more about our expectations for EDI.
Applicants planning to include international collaborators on their proposal should visit Trusted Research for guidance on getting the most out of international collaboration while protecting intellectual property, sensitive research and personal information.