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Artificial Intelligence for Multiple Long-Term Conditions (AIM) - Frequently Asked Questions


Published: 01 July 2020

Version: 1.1 - June 2021

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This document outlines answers to questions frequently asked by applicants to the Artificial Intelligence and Multiple Long-term Conditions (AIM) call. The answers covers the Research Collaboration and Development Awards only. More information is available in the call research specification.

Will the COVID-19 lockdown impact the start and end date of this project call?

The timetable for this funding call has been designed with COVID-19 in mind and we are not expecting any further changes. We will keep this under review and communicate any changes through the usual channels as soon as possible.

How many projects will be funded through this call?

We will be funding Research Collaborations based upon scientific quality and value for money. We expect to fund between 4-6 Collaborations. However, there is flexibility in this and the final number of Collaborations funded will depend on the size of successful applications. Value for money will be one of the assessment criteria and Collaborations will need to justify their costs in full. We are looking to fund a balanced portfolio, with a spread of risk profiles. 

Is it possible to see winning proposal examples to have a better idea about the structure, and expected research and development balance of the NHIR proposals?

This is a new and bespoke call, therefore it is not possible to provide examples of funded proposals. 

Is it possible to get advice on a draft research proposal?

The NIHR Research Design Service (RDS) provides support to health and social care researchers across England on all aspects of developing and writing a grant application including research design, research methods, identifying funding sources and involving patients and the public. Advice is confidential and free of charge.

Is it OK to allocate funding for cloud computing resources?

NIHR will fund costs necessary for undertaking the research, including cloud computing. T&Cs of cloud computing services will need to be in line with the T&Cs of the NIHR contract.

What is meant by MLTC? 

Multiple long-term conditions (MLTC) refer to the co-existence of two or more long-term conditions. The full definition can be found in the research specification and the NIHR strategic framework for MLTC-M research.

What is the difference between multimorbidity and comorbidity? Are both in scope for this call? 

Patients do not like or understand the term ‘multimorbidity’. The NIHR is using the term ‘multiple long-term conditions (multimorbidity) (MLTC-M)’ as the term multimorbidity has impetus following the Academy of Medical Science report in 2018. MLTC-M and comorbidity provide two different perspectives through which to consider a patient with more than one concurrent condition. Comorbidity is the presence of one or more additional conditions co-occurring with (that is, concomitant or concurrent with) a primary, or index, condition. Whereas a multimorbidity or MLTC approach does not have an index or primary condition. The NIHR is particularly interested in what has been termed complex multimorbidity (four or more long-term conditions); research on clusters of conditions linked to an index condition (co-morbidity) is not in scope for this call. It would need to fit with the call’s focus on identifying new and exploring under-researched clusters rather than those which are already well defined.

How many conditions should be included in an application?

There is no specific target or limit on the number of conditions that should be included; it will depend on the research questions the project is seeking to answer. However, the call is looking to identify new and ‘complex’ clusters of multiple long-term conditions rather than those clusters which are already well defined. 

Are neurological conditions included in the definition of MLTC? Do long-term conditions include Autism Spectrum Disorders?

Yes, both neurological conditions and Autism Spectrum Disorders would be in scope as long-term conditions, which could form part of a cluster of MLTC. 

What is the definition of Artificial Intelligence that will be used in the context of this call? 

Artificial Intelligence is the use of digital technology to create systems capable of performing tasks commonly thought to require ‘intelligence.’ A full definition is outlined in the research specification.

What stage of development does the AI need to be at to be funded and to be achieved by the end of the funding? Is proof of concept acceptable or does there need to be evidence of real-world application or effectiveness?

This call is focused on developing AI technologies to identify new clusters of conditions and explore trajectories in the development of clusters of conditions over time. Given this focus, projects are unlikely to lead to clinical application of AI technologies over the duration of the funding period. However, this will be assessed on a case by case basis. 

For departments/applicants that have not previously worked with AI, will you offer guidance as to who we can collaborate with?

The NIHR will offer networking and engagement events to bring together researchers from a range of disciplines over the summer. The NIHR RDS provides support to health and social care researchers across England on the guidelines around proposal collaborators.

Could research focusing on AI assisted therapy or robotics for people living with Multiple Long-Term Conditions be in scope?

This call is for research to use AI and data science techniques to identify and understand clusters of MLTC and their development over time. Projects focusing on AI assisted therapy or robotics would not be in scope. 

Are large cohort studies aimed at image collection integrated in real world practice allowed as part of the call?

This call will fund programmes of research which seek to develop and use AI and data science techniques to identify and understand clusters of MLTC and their trajectories over the life course. Collaborations will need to add significant new knowledge of clusters generated through the application of AI and data science techniques to be in scope. 

Would rare diseases that affect multiple systems be in scope? 

The NIHR Strategic framework for MLTC-M research published alongside this call outlines what NIHR means by the term ‘multiple long-term conditions’. We appreciate that many rare diseases affect multiple systems, and therefore would be within scope for consideration in NIHR MLTC-M research. The specific aim of this call is to use AI to identify and understand clusters of multiple long-term conditions and funded projects would need to have this as the primary focus.

How far is global health research within scope for this call?

Research funded through this call needs to produce knowledge which is relevant to the health and care system in the UK. This does not rule out research involving international collaborations or drawing on international data sources – as long as it is reasonable to think that the findings would be relevant in the UK context, or would derive relevant learning for the UK. Collaborations working solely on global health research or conducting research in contexts which are very different to the UK would not be in scope. 

The scope focuses on patients with complex MLTC-M (four or more conditions); however certain high-risk groups for multimorbidities are identifiable before overt disease presentation - are these considered in scope?

Research which uses AI and data science techniques to identify and understand trajectories or development of clusters of conditions over the lifetime would be in scope for this call. We want to see applications which focus on identifying and understanding new or under-researched clusters. Endotypes, in addition to phenotypes, would be in scope to identify clusters . Precursors to disease such as obesity are also in scope. Research looking at trajectories or development of clusters over time could start with retrospective data including populations which do not yet have MLTC-M. Research proposals which focus solely on high-risk groups for those clusters which are already well defined are unlikely to be competitive.

What balance is sought between projects which develop a high quality MLTC data resource for broader stakeholder use versus answering specific questions in MLTC using AI approaches? 

The funded Collaborations need to generate new knowledge of clustering in MLTC. Collaborations focusing solely on developing high quality MLTC data would not be in scope for this call. We do appreciate that the generation of new knowledge on clusters will require development work to ensure data sources are suitable. We want to support open access and sharing of data linkage expertise where possible and will be assessing applications on how they propose to do this over the lifetime of the award. 

Are there any specific disease areas that you are prioritising? Are there any clusters of conditions or types of MLTC that are a priority?

This call is particularly focused on the identification of new clusters, or research into clusters which are not already well defined and researched. We are not prioritising any specific disease areas – we are interested in MLTC-M, and in what has been termed complex multimorbidity.  

Are there any specific groups of people, apart from older people, in which the funder would like research to focus, or is the brief open in this regard? 

While MLTC-M is more prevalent in older people, this call takes a life-course approach from pregnancy and paediatrics through to older age. There are no specific priority groups we would expect applicants to include but we are particularly interested in groups with four or more MLTC (complex multimorbidity), who are under-represented in research, with the greatest burden from living with their conditions, and those living with deprivation. 

How does this fit with the MRC / NIHR SPF call on ‘tackling multimorbidity at scale’?

There is overlap between the AIM call and the joint NIHR-MRC call, ‘Tackling Multimorbidity at Scale’. This call is designed to complement the research funded through the joint call but call specifically aims to bring in researchers with expertise of AI, including machine learning. We continue to take a biopsychosocial perspective, as for the joint call, but there are some differences: basic science on mechanisms underpinning clusters of MLTC are out of scope for this call; and we are also ruling out research on co-morbidity to an index condition. We would like to see applications on new cluster identification and mapping, and further research on understanding trajectories of new and identified clusters. The outcomes from the first funding panel of the SPF call have been published on the MRC website and outcomes from the remaining funding panels will be published as soon as is feasible.

Is it suitable for early career researchers to apply for a Research Collaboration? 

Early career researchers can apply for Research Collaborations, but we recommend that significant senior support is provided to less experienced researchers. We expect Collaborations to be complex awards requiring well developed leadership and organisational skills for successful delivery. 

Which disciplines or backgrounds are you looking for leadership/PIs for the call?

It is the responsibility of the applicants to determine the most suitable background and expertise required to lead a project. The type of experience and skills needed will likely depend on the research questions the proposal is trying to answer. We are looking for multidisciplinary teams to bring a wide lens to questions but open to all as PIs.

Do those applying directly for a Research Collaboration award need to have a proven record (e.g. of joint outputs)? Do all members of the Collaboration have to be existing members, or can it be expanded? 

We are looking to build capacity in the field of MLTC-M research and appreciate that as we are asking multidisciplinary teams to come together in way they may not have worked before, not all groups will have a proven record. Applications should set out how they intend to work together with partners and provide a clear structure that can meet the vision and the objectives set out in their programmes of work. The funding panel will reserve the right to suggest that applications that require further be rerouted to be considered for a Development Award to allow further time to progress their thinking, proof of concept and develop networks. Collaborations can be expanded between stage 1 and 2 of the commissioning process but should have the relevant expertise in place to begin if funded. 

Are applicants from regional groupings welcome or are national grouping preferred? 

We do not have a preference for either national or regional Collaborations. The groups that come together should include the expertise needed to answer the aims of the programme of work.

Would you accept multiple applications from a single institution? Can applicants be on more than one application? 

We will accept multiple applications from a single institution. Applicants may put their names to more than application but should consider whether they feasibly have the capacity to deliver on both projects. We do not anticipate anyone would be a Principal Investigator on more than one Collaboration.

Is it possible to include co-Is from other countries in Collaborations? 

It is possible to include co-Investigators from other countries.

Would you welcome industrial Collaborations in this initiative? Will you fund SMEs? 

Collaboration with industry or trade representative bodies is encouraged and we expect this to lead to, for example, access to complementary AI tools, techniques, expertise and data sources. SMEs are eligible to compete for funding. Receipt of funding will be subject to the T&Cs of the NIHR Contract. An example of NIHR contract for commercial organisations can be found on the sign a contract webpage.

What is the NIHR approach to working with commercial organisations when IP rights are a central issue? 

Applicants are advised to review the NIHR Intellectual Property and Commercialisation Guidance. Please note these are guiding principles. In all circumstances, the NIHR seeks to ensure that arising Foreground IP is exploited where possible and appropriate to achieve public and patient benefit.

Are you expecting PPI in the development of the actual application (for the Development Awards and for the Research Collaboration grants), or a description of plans for the proposed research in the application? 

As per NIHR guidance on public involvement in NHS, health and social care research, we expect to see PPI embedded throughout the timeline of the programme of work, from inception (including application development) through to dissemination. 

Can a portion of the research collaboration grant be to cover the costs of co-production / patient & public involvement and engagement?

Yes. PPI should be fully costed and embedded throughout the grant. The can include co-producing and developing the research questions and project design, including project management staff costs. Guidance on costing PPI is available on the NIHR website.

Where should I include the details on engagement with the Research Support Facility?

The activities related to the engagement with the AIM  Research Support Facility has to be included in Section 8 -  The detailed research Plan, under the research plan/ methodology subsection. You can also use the project management subsection to explain how your team will work with the Research Support Facility (RSF) which may include activities related to data facilitation via trusted research environment, sharing software and analysis with the research community, reproduced research artefacts, interoperable infrastructure, data curation, quality control and sharing the expertise of your team with AIM research community.


Who has the authorisation rights to enter the data and edit  the online application form?


Only the co-applicants (up to 20 in total) are able to enter the data to sections of the online application and edit the application. Chief Investigator (Lead Applicant) is provided with final submission rights of the online application, co-applicants cannot submit the application. To be selected as a co-applicant, users have to be registered and approved on the RMS system. Following the RMS registration the user will be granted access within 2 working days.


Will the feedback points from my Development Award/Stage 1 application be automatically pre-populated  in the section "changes from first stage" ?


Wave 2 of the Artificial Intelligence for Multiple Long-Term Conditions (AIM) Call is administered as a Stage 2. In the section "changes from first stage" you will find the notification "The attached file contains the feedback points from your Development Award/Stage 1 application". Please note that the file will not be  pre-populated in your application form . Please complete this section manually in the "Changes from Stage 1" section by submitting up to 3700 words.


What are the differences between a Co-Applicant and Collaborator and where can I include the information about Collaborator?

Co-applicants are those individuals with responsibility for the day-to-day management and delivery of the project. Co-applicants, including public co-applicants, are considered part of the project team and are expected to share responsibility for its successful delivery. In contrast, collaborators normally provide specific expertise on particular aspects of the project but who do not share in the responsibility for the delivery of the project. Collaborators together with their institutions could be mentioned in the “Detailed Research Plan section” where you can explain their role and scope of work.  Individual Collaborators and collaborative institutions may have a budget section in the online application or may not have this budget section in case their work is funded from another funding source which is not related to the NIHR AIM Wave 2 application.