Call for Proposals

AIM-AHEAD Consortium Development Program (CDP)

Fostering Trustworthy AI Research to Advance Health and Medicine for All Americans (FAIR-MED)

Overview

The Fostering Trustworthy AI Research to Advance Health and Medicine for All Americans (FAIR-MED) program funds multi-disciplinary research that develops and implements Artificial Intelligence/Machine Learning (AI/ML) to address differences in health outcomes related to cancer, cardiometabolic and behavioral health. Health outcomes refer to the broad range of measurable and perceived changes in the health status of individuals or populations that result from health-related factors, interventions, environments, and non-clinical factors.  These outcomes encompass physical, mental, and societal well-being, and reflect how health is experienced, maintained, or improved across time. The FAIR-MED Call for Proposals (CFP) addresses the limitations of many AI/ML models implemented in clinical settings, which were not designed to incorporate trustworthy AI principles or actively engage a broad range of stakeholders including healthcare providers and patients. Successful FAIR-MED projects will need to engage healthcare providers, including but not limited to those serving patients in Federally Qualified Health Centers (FQHCs), Community Health Centers (CHCs), or Medically Underserved Areas (MUAs). FAIR-MED projects are expected to design and field-test AI/ML tools, models or AI-aided interventions, while integrating trustworthy AI considerations throughout design, development, and implementation. As outlined in the AIM-AHEAD principles, a community-engaged design phase grounded in trustworthy AI principles is required for all funded projects, with ongoing engagement and bidirectional communication between AI/ ML developers and healthcare collaborators (e.g., health care professionals or patient representatives) throughout the project.

About AIM-AHEAD

The AIM-AHEAD Coordinating Center (A-CC) was established to foster broad representation in the field of AI/ML, with an emphasis on promoting health for all Americans. We aim to achieve this objective by engaging in a fair and transparent process of building a consortium of AI/ML to advance health across all American communities and broaden participation in the AI/ML workforce. Many communities have untapped potential to contribute new expertise, data, recruitment strategies, and cutting-edge science to the AI/ML field. To promote health for all, the A-CC seeks to increase participation and engagement in AI/ML through mutually beneficial partnerships, stakeholder engagement, and outreach.

The A-CC includes four cores to support AIM-AHEAD investigators:

The Leadership/Administrative Core leads the A-CC, recruits and coordinates consortium members, project management, partnerships, stakeholder engagement, and outreach to develop AI/ML talented researchers in health research, and establishes trusted relationships with key stakeholders to enhance the volume and quality of data used in AI/ML research. The Leadership/Administrative Core operates as a Pass-Through Entity for the FAIR-MED program.

The Data Science Training Core assesses, develops and implements a robust data science training curriculum and workforce development resources in AI/ML.

The Data and Research Core addresses research priorities and needs by linking and preparing multiple sources and types of research data, forming an inclusive basis for AI/ML use cases that illuminates strategies and approaches to address health problems. To accomplish its mission, the Data and Research Core facilitates the extraction and transformation of data from electronic health records (EHR) and data on lifestyle contributors to health for research use.

The Infrastructure Core assesses data, computing and software infrastructure models, tools, resources, data science policies, and AI/ML computing models to facilitate AI/ML and health research; and establishes pilot data and analysis environments to accelerate overall A-CC aims.

Details on AIM-AHEAD resources are in the Appendix.

AIM-AHEAD North Stars

Projects must be aligned with one or more of the AIM-AHEAD North Stars: 

North Star 1: Develop a representative AI/ML workforce with broad participation.

North Star 2: Increase knowledge, awareness and national-scale community engagement and empowerment in AI/ML. 

North Star 3: Use AI/ML to improve behavioral health, cardiometabolic health and cancer outcomes for all.

North Star 4: Build community capacity and infrastructure in AI/ML to address community-centric health needs and challenges. 

Purpose/Objectives

The primary objective of the FAIR-MED program is to support the development of multidisciplinary research projects involving partnerships with relevant collaborators (e.g., health care professionals or patient representatives) that leverage AI/ML to promote health for all Americans by utilizing novel algorithms or approaches grounded in trustworthy AI.

FAIR-MED projects are expected to significantly impact healthcare access and utilization, healthcare quality and value, and health outcomes for populations that are disproportionately impacted by cancer, cardiometabolic disease and behavioral/mental health disorders. Meritorious projects will be funded to establish collaborative partnerships with relevant stakeholders. Applications that lack stakeholder partners or do not assess or evaluate the integration of responsible AI/ML principles into project design, development and implementation, will be considered non-responsive to this CFP.  FAIR-MED project teams are expected to design, plan, and conduct projects meeting each of the following requirements:

• Engage health care settings and patient representatives in planning trustworthy AI/ML development, implementation and assessment.
• Demonstrate feasibility of translating trustworthy AI/ML tools or algorithms into clinical or public health or operational practice with potential to improve health outcomes for AIM-AHEAD North Star III health categories (i.e., cancer, cardiometabolic and behavioral/mental health).
• Augment the shared learnings of the AIM-AHEAD Consortium through the engagement of broadly representative, interdisciplinary project teams committed to tangible deliverables to advance health for all.

Addressing Trustworthy AI/ML

Proposals to the FAIR-MED program must include a plan for ensuring the project is guided by consideration of the social, legal and socio-economic implications of AI/ML. These considerations include, but are not limited to:

1. Variations in datasets, algorithms, and applications;
2. Patient privacy in the data and the developed AI/ML solutions;
3. Trustworthy use of data from electronic health records, wearable devices and/or medical imaging; 
4. Safeguarding against the unintended or adverse social, individual, and community consequences of research on, and implementation of, AI/ML solutions.

FAIR-MED program applicants are encouraged to propose projects that explicitly address one or more of the considerations listed above. All FAIR-MED projects are expected to work with the Infrastructure Core to develop an initial review and plan for their project within the first 4-6 weeks of support, and to participate in at least two Infrastructure Core forums during the period of the award.

At the end of the Period of Performance, FAIR-MED project teams will be required to deliver a detailed plan for scaling the field-tested innovations into future interventional studies and/or projects to build AI/ML capacity in the partner institution(s) and similar settings/communities. This plan must also address future monitoring of datasets, algorithms, and other potential artifacts to ensure ongoing adherence to best practices in AI/ML utilization, such as monitoring for algorithm model drift, managing institutional challenges in capacity, and adhering to regulatory changes.

In summary, the FAIR-MED CFP seeks to catalyze collaborative partnerships to assess and/or evaluate the integration of AI in a trustworthy manner that adheres to the principles of co-design. Applications should demonstrate potential to improve healthcare and outcomes in alignment with AIM-AHEAD North Star (III):

• Use AI/ML to improve behavioral health, cardiometabolic health and cancer outcomes for all.

Project Guidance

Applicants must propose projects that engage healthcare collaborators (e.g., health care professionals or patient representatives) to identify and promote trustworthiness in AI/ML and improve health outcomes. Examples of the types of research projects that are expected to emerge through this opportunity include, but are not limited to:

• Examination of the extent and impact of community engagement on data collected and/or research design for the creation or application of AI/ML
• Use of broadly representative population data to generate AI/ML models
• Documentation of the institutional challenges or barriers that arise during the course of research on AI/ML and, if applicable, testing solutions to address them
• Developing human-centered and/or values-sensitive approaches to the creation and application of AI/ML
• Fostering an understanding of how to detect and prevent AI/ML models from inducing differences in health outcomes between subpopulations
• Implementing multi-modal AI (e.g., incorporating EHR, medical imaging and wearable devices) to enable a more comprehensive evaluation of patient health
• Improve health care operations and/or patient outcomes through AI-assisted prevention, diagnosis, treatment, strategies in alignment with the AIM-AHEAD North Stars
• Defining and addressing key aspects of trustworthy AI/ML, including patient privacy, algorithmic explainability, and transparency in decision-making
• Promoting efficacy and timeliness of engagement with participants and communities by applying trustworthy AI principles to improve health for all.

Organizational Structure and Nature of Collaboration Among the Required Partners

Organizational structure: The team structure should avoid assigning any single individual undue authority that prevents contributions from the wider team for setting program priorities, resource distribution, and rewards. Strong leadership is required for complex team efforts to succeed, while at the same time effective team leadership requires decision-making based on an amalgam of interests, expertise, and roles, guided by recognized project objectives. Applicants are encouraged to develop a project objective-based management structure that effectively promotes the proposed research.

Nature of the Collaboration: A framework for sharing and/or integrating data across team members must be customized to fit the specific data needs of the project. Plans for data archiving and long-term preservation for team use should be described in the proposal (See Partnership Plan Section). Depending on the needs and challenges of managing team data, applicants may also include and justify data/resource sharing and management systems and/or hiring of professional data science staff.

Important Notice

Consistent with NIH/HHS policies and applicable law, AIM-AHEAD programs do not use the race, ethnicity, or sex of prospective program participants or faculty as an eligibility or selection criteria. The race, ethnicity, or sex of candidates will not be considered by AIM-AHEAD in the application review process or when making funding decisions.

Eligible Organizations

Higher Education Institutions

• Public/State Controlled Institutions of Higher Education
• Private Institutions of Higher Education

Nonprofits Other Than Institutions of Higher Education

• Nonprofits with 501(c)(3) IRS Status
• Nonprofits without 501(c)(3) IRS Status

For-Profit Organizations

• Small Businesses
• For-Profit Organizations (Other than Small Businesses)

Local Governments

• State Governments
• County Governments
• City or Township Governments
• Special District Governments
• Indian/Native American Tribal Governments (Federally Recognized)
• Indian/Native American Tribal Governments (Other than Federally Recognized).

Other

• Independent School Districts
• Public Housing Authorities/Indian Housing Authorities
• Native American Tribal Organizations (other than Federally recognized tribal governments)
• Faith-based or Community-based Organizations
• Regional Organizations

The primary applicant organization must be a domestic institution/organization located in the United States or its territories.

Before applying, these organizations must be registered with System for Award Management (SAM; see https://sam.gov/content/home) and must maintain active SAM registration throughout the award period (please see below for required registrations).

Foreign Institutions

Non-domestic (non-U.S.) Entities (Foreign Institutions) are not eligible to apply.

Non-domestic (non-U.S.) components of U.S. Organizations are not eligible to apply.

Foreign components, as defined in the NIH Grants Policy Statement, are not allowed.

Required Registrations

Applicant Organizations

Applicant organizations must complete and maintain the following registrations as described in the SF 424 (R&R) Application Guide to be eligible to apply for or receive an award.  All registrations must be completed prior to the application being submitted.  Registration can take 6 weeks or more, so applicants should begin the registration process as soon as possible.  The NIH Policy on Late Submission of Grant Applications states that failure to complete registrations in advance of a due date is not a valid reason for a late submission.

System of Award Management (SAM): Applicants must complete and maintain an active registration, which requires renewal at least annually.  The renewal process may require as much time as the initial registration.  SAM registration includes the assignment of a Commercial and Government Entity (CAGE) Code for domestic organizations that have not already been assigned a CAGE Code. Federally recognized tribes and their derivatives are exempt from this requirement.

NATO Commercial and Government Entity (NCAGE) Code: Foreign organizations must obtain an NCAGE code (in lieu of a CAGE code) in order to register in SAM.

Unique Entity Identifier (UEI): A UEI is issued as part of the SAM.gov registration process.  The same UEI must be used for all registrations, as well as the grant application.

Grants.gov registration: Applicants must have an active SAM registration in order to complete the Grants.gov registration.

Eligible Applicants (Program Director/Principal Investigator)

Any individual(s) with the skills, knowledge, and resources necessary to carry out the proposed research as the Program Director(s)/Principal Investigator(s) (PD(s)/PI(s)) is invited to work with his/her organization to develop an application for support.  For institutions/organizations proposing multiple PDs/PIs, please consult the Multiple Program Director/Principal Investigator Policy and submission details in the Senior/Key Person Profile (Expanded) Component of the How to Apply – Application Guide.

AIM-AHEAD multi-award restrictions

Individuals may NOT hold multiple AIM-AHEAD awards at the same time. Consequently, the following limitations apply:

• Applicants to multiple AIM-AHEAD programs may receive only one award. When an applicant to multiple AIM-AHEAD programs is recommended for more than one award, AIM-AHEAD will determine which award the applicant will receive.

• An applicant currently participating as an awardee, trainee, fellow, or PI in an AIM-AHEAD program, and whose current award is still active at the start of the second program, is not eligible to receive the second award. 

An applicant serving as PI on a current AIM-AHEAD award is not eligible to hold multiple AIM-AHEAD research awards.

Application Key Dates

Project Milestones

The 24-month proposals must include the following phases and target timelines:

• Months 0-6: Collaborator-engaged design and development
• Months 4-6: Trustworthy AI plan
• Months 7-18: Community-engaged intervention
• Months 19-24: Community-engaged plan for sustainability, scalability, and ethics monitoring.

Project Sustainability

At the end of the Period of Performance, awardees must deliver a detailed plan to further scale the innovation in a future interventional research study or project to meet the goals of the Program. This plan must address scale-up and sustainability. Applicants to this solicitation are encouraged to propose other tangible artifacts (e.g., lessons learned document for AIM-AHEAD Consortium, code released to GitHub, trustworthy AI practices, datasets made available in NIH-designated repository, presentations, and manuscripts).

1. Title: The title should describe the project in concise, informative language.
2. Project Summary/Abstract (1-page limit): Provide a succinct description of the proposed work including the project’s long-term objectives, and a description of the research design and methods for the entire AI/ML project.
3. Project Description: The project description should contain the following components adhering to the page limits.
• Specific Aims (1 page): Provide a clear, concise summary of the aims of the work proposed and its relationship to your long-term goals. State the hypothesis to be tested and anticipated outcomes or benefits upon successful completion of the project.
• Research Plan (5 pages)
  • Background and Significance: Summarize the background and state the problem this proposal will address. Summarize important findings of the applicant and others in the same field, critically evaluating existing knowledge. Identify gaps that this project is intended to fill. State concisely the importance and relevance of the research to community-engaged AI/ML and research into differences in health outcomes. Describe the populations of interest. Also, it is incumbent upon the applicant to make a clear link between the project and AIM-AHEAD North Star III. The significance section will be assessed in terms of the potential impact on the AIM-AHEAD mission, and will be factored into the overall priority score as noted in the peer review criteria.
  • Preliminary Studies: Concisely describe previous work performed by the applicant related to the proposed research that will help to establish the experience and competence of the investigator to pursue the proposed project. Include pilot studies showing the work is feasible. (If none, please state this to be the case.)
  • Community-Engaged Research Design and Methods: Describe the envisioned research project and plans to engage the collaborating organization in the project development and implementation. Describe any community engagement methods, and how your research idea innovates or has an advantage over existing methods/applications and brings together different disciplines. Applicants must explain how relevant non-clinical factors are factored into the research design, analysis and reporting. Furthermore, describe the infrastructure modality that would be used, data sources needed and used, computing infrastructure needed and used (see data and infrastructure section).
    Integration of trustworthy AI principles and practices and active engagement with communities throughout every stage of the project life cycle, including design, development, and practical implementation: Describe plan for ensuring work is guided by plans to ensure the trustworthiness of AI/ML, including but not limited to (1) the datasets, algorithms, and applications involved; (2) ensuring privacy and data protection (3) evaluating impacts on individuals and communities; 4) reducing variation in health outcomes; and 5) establishing mechanisms for continuous evaluation and stakeholder engagement to refine trustworthy AI practices.
  • Describe any prior collaborations of relevance and strategies for active participation of partners in this project. Furthermore, the proposal should clearly articulate the goals of the project and expected outcomes in terms of collaboration and partnership, project plan, research products and other artifacts.
  • Data: Applicants are encouraged to use data from a healthcare provider’s EHR. Applicants must describe (1) reference(s) to the data under consideration and reasons for this choice; (2) the potential impact of scientific advances that could be made from AI/ML applications developed with the data; (3) proposed methods/data modalities to be used; (4) how the data will be made available to AI/ML applications and researchers, for example, through NIH repositories, NIH knowledge bases, or other data sharing resources including those appropriate for controlled access data, and (5) how the legal and social implications of data will be identified and addressed.
  • Consortium Development: Applicants are required to describe how the proposed project teams will engage and collaborate with the AIM-AHEAD community (e.g., contribute to documentation and training resources, welcome and empower new users, help foster a representative community, and integrate practices that promote trustworthiness of AI/ML, such as promoting privacy, transparency, and accountability. Also, applicants should describe their plans for sustaining the AI/ML and collaborations(s) after the project period ends.
4. References Cited (maximum 3 pages): List only references cited in the Project Description or supplementary documents of the proposal.
5. Detailed Budget and Budget Justification: Prepare your budget using NIH R&R Form. The budget justification should entail a narrative explanation of each of the components of the cost required of the proposed work. The budget explanation should focus on how each budget item is required to achieve the project’s objectives and how the estimated costs in the budget were calculated. Travel to the AIM-AHEAD annual meeting (July/August each year) should be included in the budget.
6. Facilities, Equipment and Other Resources: Facilities, Equipment and Other Resources should describe the resources needed and those that are available to the applicant and collaborators for the proposed research project. Please also describe cloud compute resources required for the proposed project, if applicable. Applicants should convey how the scientific environment in which the research will be conducted contributes to the probability of success. Equipment is generally not allowed on these projects.
7. Senior Personnel Documents:
   • Biographical Sketches: Biographical sketches in NIH format or resumes (5-page limit) or 5-page CVs are required for the PI, any co-PIs, and each of the participating Senior Personnel listed in the Project Description (including postdocs, staff, and /or students.
   • Current and Pending Support: Each PI(MPI), any CoIs/collaborators, and each of the participating Senior Personnel listed in the Project Description (including postdocs, staff, and /or students) must disclose any previous funding from NIH or AIM-AHEAD or Federal sources over the past 3 years. If none, please state "None."
   • Collaborators and Other Affiliations Information: Provide the names of collaborating organizations, their tax status, and their roles in the proposed project.
8. Human Subjects Research
   • Provide an explanation for any use of human specimens and/or data not considered to be human subjects research.
   • If the proposed research requires a Data Use Agreement or other agreement(s) for data use, provide the plan for executing among all partners/collaborators.

   Definition of Human Subject: A living individual about whom an investigator (whether professional or student) conducting research: (1) obtains information or biospecimens through intervention or interaction with the individual, and uses, studies, or analyzes the information or biospecimens; or (2) obtains, uses, studies, analyzes, or generates identifiable private information or identifiable biospecimens. [45 CFR 46.102(e)].

9. Other Required Documents:
• Institutional Need and Support Statement (up to 2 pages). This statement must be signed by the applicable leadership of the institution (e.g., CEO, Director, University president, provost or college/school dean, vice president of research). The statement must demonstrate support for the partnership and commitment of additional resources necessary to ensure the maximum sustainability of the partnership. This statement should include the following:
  • Assessment of the institution’s commitment to AI-driven solutions, its current AI research and education, and/or its data and infrastructure capacity;
  • A statement of commitment of institutional support for the proposed activities including specific resources, space, protected time, etc. These statements should also identify the specific number of positions that are wholly dedicated to AI data and infrastructure under the proposed partnership. In addition, if American Indians are involved, a Letter of Commitment from the Tribal Nation Leader is required.
  • Describe the proposed research involving human subjects, human specimens, and/or data obtained in human subjects or patients (including EHR and/or repository data), if applicable.
• Letter of collaboration: This letter from at least one collaborator will describe the collaborating institution’s contributions to the project. The letter should include commitments and support to the project from collaborators’ organizations' leaders, including resources such as data and expertise. It should also explain how this project will advance the collaborating organizations' goals. It is highly recommended that the Co-PI be from a healthcare organization.
• Results from Prior NIH/AIM-AHEAD Support. If applicable, the applicant must submit the Results from prior NIH/AIM-AHEAD support as a supplementary document, not as part of the Project Description. This approach allows the applicant to maximize the use of the page allowance to describe the proposed activities.
10. Budget

    Funding Period

    Applicants may request up to 2 years of funding support commensurate with project scope. Include project personnel from both the host institution and partner organization(s) (required).

    Funding Limit

    AIM-AHEAD anticipates supporting approximately eight Consortium Development projects, each with a budget cap of $800,000 total costs for a 24-month period to plan and conduct community-engaged, health- centric, trustworthy AI research projects to meet the objectives of the program. This cap includes indirect cost allowances. Funding for months 13-24 will be contingent on timely completion of project milestones and progress toward project aims, as reported in the monthly progress reports (see Awardee Expectations, p. 17).

Sample Budget Template

Budget: Year One

Allowable costs

• Academic Institutions: The award may be used for salary and fringe benefits of the Multiple Principal Investigators (MPIs), collaborating investigator(s), and other participants with faculty appointments, consistent with percent effort, and for project-related expenses, such as salaries of technical personnel essential to the conduct of the project, supplies, equipment, computers/electronics, domestic travel, volunteer subject costs, data management, and publication costs, etc. Tuition support for graduate students may also be requested.
• Other non-Academic Institutions/Organizations: The award may be used for salary and fringe benefits of the Multiple Principal Investigators (MPIs), collaborating investigator(s), and other participants consistent with salary structure, and for project-related expenses, such as salaries of technical personnel essential to the conduct of the project, supplies, equipment, computers/electronics, domestic travel, volunteer subject costs, data management, and publication costs.

Awardees are expected to attend the AIM-AHEAD Annual Conference to be held in July or August at a location to be determined. The budget should include anticipated travel expenses to attend the conference.

Unallowable costs:

• Funds to support general staff or administrative support
• Funds to support international travel

Assessment of the application’s scientific merit will be guided by the following specific questions related to the proposed project:

Alignment with program:

1. Does the proposal engage one or more collaborators (e.g., healthcare provider or patient representatives)? Are specific strategies for effective collaboration between partners described in the proposal?
2. Is there evidence of the collaborators’ involvement in developing the proposal?
3. Does the proposal develop novel algorithms or methods to improve understanding and outcomes for behavioral health, cardiometabolic health, or cancer?

Trustworthy AI/ML Principles:

4. How well does the project collect empirical evidence about the application of trustworthy and/or transparency principles in the design, development, and/or use of AI/ML and their impact on addressing health outcomes?
5. How well does the project collect information about challenges in the design, development, and/or use of AI/ML and their impact on addressing health outcomes in their institution?
6. Does the team describe plans to identify, develop, and evaluate strategies to overcome any anticipated challenges?

Expected outcomes:

7. Does the proposal clearly articulate the goals of the project and expected outcomes in terms of collaboration, partnership, project plan, research products or other artifacts?
8. To what extent is the proposed approach likely to achieve the goals of the project?
9. Does the proposal include a sustainability plan for the AI/ML after the project period ends?

Team qualifications:

10. Does the study team include a PI/Co-PI from a healthcare organization?

Consortium development/scalability:

11. Does the applicant indicate willingness to engage and collaborate with the AIM-AHEAD community, contribute to documentation and training resources, welcome and empower new users, and help foster a representative community?
12. Does the proposal demonstrate how the selected dataset(s) and/or AI/ML application(s) will result in knowledge transfer to\the AIM-AHEAD ecosystem as a whole?

Review Process

A Review Committee composed of AIM-AHEAD Consortium members will oversee the following steps and criteria to evaluate proposals and recommend award recipients to NIH, which makes the final decision on awards.

Compliance review: Program staff will do an initial check of applications for compliance with requirements of this Call for Proposals. This process may result in request for remediation and/or rejection of a proposal prior to Scientific Review and Programmatic Evaluation.

Scientific evaluation: A panel of reviewers will apply standard NIH scoring ranges (1-9) to each application on each of the eleven scientific merit criteria listed above.

Programmatic evaluation: It is expected that approximately eight awards will be assigned to the highest-scoring applications based on Scientific Merit and that additional awards potentially could be recommended for NIH consideration based on both Scientific Merit scores and Programmatic Evaluation considerations. The consortium will take steps to avoid any conflicts of interest with reviewers or voting MPIs.

Applicants will receive their scores and notes from the Scientific Merit reviewers via program administration.

Please note that, consistent with NIH practice and applicable law, funded programs may not use the race, ethnicity, or sex of prospective program participants or faculty as an eligibility or selection criteria. The race, ethnicity, or sex of candidates will not be considered by NIH in the application review process or when making funding decisions.

Awardee Expectations

Awardees are expected to develop novel or apply existing best practices for AI/ML approaches that incorporate collaborators across a broad range of constituencies, e.g. healthcare providers, patients, and advocates. Therefore, the following will be expected of the awardees:

Participation and Reports

• Awardees will participate in monthly awardee meetings (via Microsoft Teams).
• Awardees will participate in meetings with the AIM-AHEAD Coordinating Center to inform overall AIM-AHEAD data sharing / data access strategies.
• Awardees will participate in AIM-AHEAD annual meetings.
• Awardees will act as AIM-AHEAD community ambassadors to help onboard colleagues.
• Awardees must be willing to attend and present the results of their work at future AIM-AHEAD events, and volunteer to review applications for future AIM-AHEAD programs.
• Awardees agree to have AIM-AHEAD promote the project online through websites, social media, and other communication channels.
• All awardees will be expected to participate in AIM-AHEAD activities during the year, including attending two annual program-wide meetings.
• Awardees must provide a monthly summary of the status of the proposed research milestones, challenges faced and plans or tactics to overcome those challenges, usage of funds, and next steps.
• Within one month following the project end date, awardees must provide a final report of research findings, usage of funds, and a list of publications, grant applications, articles, and conference talks emerging from the research.

Compliance and Governance

• For all research projects involving human subjects research (including secondary data analysis), awardees are expected to submit their study for review to an IRB and obtain a determination letter/response (See section Application Components section, subsection 10). Even if the projects do not involve human subjects, an IRB “letter of determination” is required. When a local IRB is not available, alternative options should be used.
• Awardees are required to obtain the Data Use/Sharing or Regulatory/Contractual Agreements required to access data needed for their research.
• Any current or future data sharing must follow relevant governance documents and agreements.
• Awardees must comply with all applicable Federal statutes (such as those included in appropriations acts), regulations and policies in addition to their institutional and state policies pertaining to research funding.

Note: No funds can be drawn from the NIH payment system and no obligations may be made for research involving human subjects by any AIM-AHEAD coordinating center site engaged in such research for any period not covered by both an OHRP-approved Federal Wide Assurance and approval from the IRB, as required, consistent with 45 CFR Part 46 and any NIH policies.

Trustworthy Use of Data

As stated above, all FAIR-MED projects are expected to work with the Infrastructure Core to develop an initial review and plan for their project within the first 4-6 weeks of support, and to participate in at least two Infrastructure Core forums during the period of the award (see Project Guidance and Project Milestones).  Project teams must also commit to participating in two Infrastructure Core-supported forums during the course of their sponsorship. These forums are designed to highlight and address challenges in the development and implementation of AI/ML and range from open office hours to moderated discussions on hot topics in trustworthy AI/ML.

Required Training/Certifications

Awardees will be expected to complete Human Subjects Research training (e.g., CITI) and any other training required by datasets they intend to use in their projects.

Appendix: Awardee Resources

Data sources and accessibility

Proposed projects are encouraged to use EHR datasets sourced from the applicant’s collaborating healthcare organization. Other supplementary data sources, including the OCHIN Database on AIM-AHEAD Service Workbench or MedStar Health EHR through the AIM-AHEAD Data Bridge (AADB), are available upon request.

Post-award, there are four key requirements for obtaining access to AIM-AHEAD Curated Data (OCHIN/AADB), with target timelines for awardees below:

1. Mandatory Human Subjects Research Training such as CITI “Human Research (Protection of Human Subjects)” and “Responsible Conduct of Research”
2. Data consultation with the data source (e.g., OCHIN or MedStar) and submission of data specifications form within 30 days of award
3. Submission for IRB approval/determination within 60 days of award
4. Signed data use agreement (DUA) and IRB approval/determination within 90 days of award

Supplementary Dataset options (more information available on below datasets/cohorts):

Other publicly available datasets:

AWS Open Datasets

More information (description and links) is available here

Funding decisions will be made by September 2, 2025.

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For direct questions regarding the Consortium Development Program, please create a Help Desk ticket:

Consortium Development Program HelpDesk