Part 1. Overview Information

Key Dates

All applications are due by 5:00 PM local time of applicant organization. 

Applicants are encouraged to apply early to allow adequate time to make any corrections to errors found in the application during the submission process by the due date.

No late applications will be accepted for this Notice of Funding Opportunity (NOFO).

It is critical that applicants follow the instructions in the Research (R) Instructions in the How to Apply - Application Guide, except where instructed to do otherwise (in this NOFO or in a Notice from NIH Guide for Grants and Contracts).

Conformance to all requirements (both in the How to Apply - Application Guide and the NOFO) is required and strictly enforced. Applicants must read and follow all application instructions in the How to Apply - Application Guide as well as any program-specific instructions noted in Section IV. When the program-specific instructions deviate from those in the How to Apply - Application Guide, follow the program-specific instructions.

Applications that do not comply with these instructions may be delayed or not accepted for review.

Part 2. Full Text of Announcement

Section I. Notice of Funding Opportunity Description

Background

Genomic medicine is being increasingly used in patient care. The utility of genomic sequencing in the practice of genomic medicine has been greatly enhanced by the categorization and annotation of pathogenic genetic variants by the American College of Medical Genetics and Genomics (ACMG). However, translational research to advance our understanding of genomic and non-genomic factors that contribute to penetrance, expressivity, and pleiotropy of variants categorized to be pathogenic or likely-pathogenic is needed for more precise and effective practice of genomic medicine. The need for increased research to develop tools to translate genomic research findings into clinical applications has been highlighted by NHGRI-convened workshops (Genomic Medicine XIII, NHGRI Machine Learning in Genomics Workshop: Tools, Resources, Clinical Applications, and Ethics).

Machine Learning (ML) and Artificial Intelligence (AI) have been used for pattern discovery and classification for several decades. Recent advances in computational resources have increased the ability of ML/AI tools to learn and discover previously unrecognized patterns from large, complex multimodal datasets. ML/AI techniques have successfully identified novel patterns in non-genomic clinical datasets, receiving FDA approval for ML/AI-enabled medical devices in fields such as radiology, cardiology, and various other disciplines of medicine.

The potential for using novel ML/AI approaches in translational genomics is facilitated by the vast amounts of multimodal data that have become increasingly available through advances in standards and policies that encourage the sharing of data in a findable, accessible, interoperable, and reusable (FAIR) manner. Utilizing FAIR multimodal data along with rich biological annotations in knowledgebases and literature to train ML/AI models could potentially improve our understanding of the impact of genomic and non-genomic contributors to disease. Furthermore, the capability of such tools to learn from new data and knowledge, complemented by rapidly evolving ML/AI methods, has the potential to increase their future applicability in genomic medicine.

Maximizing the potential of ML/AI requires thoughtful attention to the ethical, legal, and social implications (ELSI) of its use in genomic medicine and healthcare more broadly. Several areas of concern have been raised related to the use and implementation of ML/AI in healthcare. These include biases in data and algorithms leading to misdiagnosis, ambiguities in accountability for misuse of the data and tools, unintended loss of patient privacy and confidentiality, lack of adequate regulatory oversight and monitoring, legal ambiguities around intellectual property rights, overreliance on ML/AI tools in decision making, challenges in patient-provider communication, lack of patient and provider confidence in ML/AI, and  other approaches that increase health disparities. Conducting ELSI research to anticipate and address these and other ELSI issues during the development of ML/AI tools can help improve scientific rigor, reduce harm, and realize the potential for benefit across diverse populations.

For the purposes of this NOFO, the following definitions/descriptions are used:

• Artificial Intelligence (AI) refers to  the capability of a computer system to mimic human cognitive functions such as learning and problem solving.
• Consortium refers to  t he Consortium which consists of the collective group of researchers funded under this NOFO and the companion NOFO, RFA-HG-24-005 .
• Cross Validation refers to mutual validation of the ML/AI tools developed by MAGen Sites in the Consortium to validate their robustness and generalizability. Cross validation should be performed by MAGen Sites other than the Site that developed the tool using datasets distinct from those used for tool development and by users different from those at the Site that developed the tool.
• Ethical, Legal, and Social Implications (ELSI) refers to an area of inquiry that may use multidisciplinary approaches to identify and define major areas of concern associated with the advancement of genetic and genomic science and the availability of new knowledge, data, and technologies. For more information, see “ELSI Research Programme of the NHGRI”.
• Genomic Translational Research refers to integration of basic research, patient-oriented research, and population-based research performed in an academic setting that mimics clinical settings with the long-term potential for integrating into genomic medicine.
• Machine Learning (ML) refers to application of AI where mathematical models of data are used to help computers learn with or without direct instruction.
• MAGen is the abbreviation for ML/AI Tools to Advance Genomic Translational Research.
• MAGen Coordinating Center (CC) refers to t he recipient funded through the companion NOFO RFA-HG- 24-005 .
• MAGen Sites refers to  t he recipients funded through this NOFO.
• ML/AI Technologies refers to algorithms, software, or platforms for ML/AI tool development.
• ML/AI Tool refers to a validated stand-alone software package that includes ML/AI pipelines and model parameters that can be implemented and cross validated.
• Multimodal Data refers to datasets that span different datatypes and contexts (e.g., imaging, text, genomic, environment etc.).
• Pathogenic Variant refers to variant with strong clinical evidence for likelihood of causing disease.
• Primary Data Generation for ML/AI Tool Development refers to  g eneration of new primary data (in contrast to derived data which refers to existing data that has been transformed).
• Social Determinants of Health (SDOH) refers to conditions in the environments where people are born, live, learn, work, play, worship, and age that affect a wide range of health, functioning, and quality-of-life outcomes and risks.

Research Objectives, Scope, and Approach

The purpose of this Notice of Funding Opportunity (NOFO) is to solicit applications to explore the feasibility of developing Machine Learning (ML) and Artificial Intelligence (AI) tools that can enhance the accuracy and precision of predicting how individuals with pathogenic genetic variants manifest disease. NHGRI aims to establish a research Consortium, ML/AI Tools to Advance Genomic Translational Research (MAGen), to collaboratively identify both genomic and non-genomic factors influencing disease development in individuals carrying pathogenic genetic variants. The ML/AI tools will leverage existing multimodal genomic and non-genomic data and will be cross validated in genomic translational research settings to ensure the robustness and generalizability of the tools for translational purposes. In addition, the Consortium will explore the ethical, legal, and social implications (ELSI) of integrating ML/AI tools into genomic medicine through the establishment of an ELSI framework for their development and through implementation of ELSI research projects.

Funding will support each Site with multi-disciplinary teams with expertise in all aspects relevant for ML/AI tool development, including expertise with large multi-modal data types (i.e., clinical, genetics, genomics, other -omics, SDOH, etc.), familiarity with the pathogenic genetic variants and diseases proposed by the applicants, and expertise in ELSI research. NIH encourages the  recruitment of team members  from diverse backgrounds, including groups underrepresented in the biomedical, behavioral, and clinical research workforce (see NOT-OD-20-031 https://grants.nih.gov/grants/guide/notice-files/NOT-OD-20-031.html) and from various genomic and non-genomic disciplines to enhance scientific perspectives and methods.

Funded MAGen Sites will work collaboratively with each other and the MAGen CC (RFA-HG-23-005) within the Consortium to meet the goals of this RFA. Therefore, applicants should read the MAGen CC NOFO (RFA-HG-23-005) to understand the role and expectation of the MAGen CC.

Given the risks involved in achieving MAGen goals e.g., selection of suitable gene sets, drafting of a suitable framework for ELSI studies, the capability to undertake cross-validation, the challenges around converging data models among others, this (and the companion) NOFO utilizes a UG3/UH3 cooperative agreement mechanism which entails a Two-Phase, one-application approach to accomplish the goals. The focus of the UG3 Phase is the development of necessary Consortium-wide consensus around the goals identified above and other aspects that could impact achieving the goals of the MAGen consortium. The focus of the UH3 Phase (if successful) will be the actual development and execution of the consensus approach developed in the UG3 Phase. The objectives of the MAGen Sites in the two Phases are:

UG3 Phase – Design (Years 1-2)

1. Drafting the ELSI framework for Consortium-Wide ML/AI Tool Development and Cross Validation: Entails drafting an approach and set of guiding principles to be used by the Consortium across both the UG3 and UH3 Phases of ML/AI tool development and cross validation. ELSI scholars will work collaboratively with investigators across the Consortium to develop a draft ELSI framework that meets or exceeds the following expectations:
   • Identify and define ELSI issues associated with the development and use of ML/AI tools for translational genomics research.
   • Consider the perspectives of various groups who may be directly or indirectly impacted by the use of ML/AI tools.
   • Be informed by existing ELSI scholarship and frameworks.
   • Provide a systematic approach for assessing the merits and implications of decisions made by the Consortium.
2. Selecting the Consortium Gene Set for ML/AI Tool Development: Entails collaborative selection by the Consortium of the collective set consisting of a total of at least 3 human genes with pathogenic variants from the gene lists of 2-4 candidate genes that have been proposed by each of the MAGen Sites for ML/AI tool development and cross validation. Selection will be based on the variants, the associated human diseases, and corresponding human datasets accessible to the Consortium and deemed to best allow accomplishing the objectives of the NOFO. Multimodal datasets used to train the ML/AI tools could include genomics and other omics, phenotypic, SDOH, ancestry, environmental exposure, etc. Sources for such data could include public data repositories, EHRs, clinical sequencing and genetic testing facilities, and Internet of Things (IoT) sensors, in addition to published literature. Datasets and reference knowledge from other organisms may be used to complement the human data. NOTE: This NOFO will not support any new primary data generation activities for ML/AI tool development and entails the use of data readily accessible to applicants at the time of application submission. Thus, an important consideration in choosing the variants and diseases for the Consortium to focus on is the adequacy of datasets available for tool development as well as cross validation. Each Site will be responsible for developing tools for at least one gene among the gene set selected by the Consortium, and for cross validating tools developed by the other MAGen Sites for the other selected genes.
3. Defining ML/AI Tool Requirements: Entails defining the ML/AI tools’ key requirements, including model outputs and their translational relevance in relation to the selected genes and pathogenic variants. Outputs should be selected in the context of the ELSI framework developed by the Consortium and any challenges in integrating the framework into tool design and cross validation should be documented and shared within the Consortium. Importantly, and with guidance from the MAGen CC, tools should be designed to be portable to cloud environments. It is understood that the tool will be validated by site that developed the tool prior to sharing the tool for cross validation.
4. Guiding the Common Data Model Development: Entails contributing to the development of the MAGen CC-led Consortium-wide common data model and processes and best practices related to updates/maintenance of the model.
5. Preparing Datasets for ML/AI Tool Development and Cross Validation: Entails preparing the relevant datasets for development, validation, and mutual cross validation of the tools for the agreed-upon genes.  With guidance from the MAGen CC, preparation will include preprocessing and subsequent import of the dataset into the Consortium-wide common data model.
6. Designing the Consortium-Wide Plan for Cross Validation of ML/AI Tools: Entails developing the plan for cross-validation of the ML/AI tools for generalizability to include processes for:
   • Enabling cross validation in the NHGRI Analysis Visualization and Informatics Lab-space (AnVIL) or any other NHGRI-approved computational platform proposed by the Consortium. 
   • Qualitative and quantitative benchmarks of the tools. Assessment criteria may include, but are not limited to accuracy, uncertainty quantification, performance, trustworthiness, interpretability, and usability. The plan should include processes for resolution of any discrepancies in results to understand the source of discrepancy and impact on the validity of potential use of the tools in genomic medicine.
   • Ensuring that the cross validating sites assess robustness and generalizability of the tools using datasets and users distinct from those used by the MAGen Site that developed the tool.
   • Development of the cloud cross validation computing environment and providing input to the MAGen CC-led establishment of the Consortium-wide processes and best practices for updates and maintenance of the environment.
   • Consortium-wide sharing of tools and documentation to include results from the validation by the Site that developed the tool to enable comparing performances to those from cross validations.
   • Consortium-wide sharing of data preprocessing scripts to facilitate reuse.
   • Validation by different intended types of users.
7. Commencing ML/AI Tool Development: Entails piloting tool development to inform the above activities and to prepare for full development of tools in the UH3 Phase.
8. Identifying ELSI Research Projects: Entails development of research questions and outcomes that should be assessed by investigators across the Consortium during the UH3 Phase. During the UG3 Phase, ELSI research projects should be designed collaboratively across the Consortium, under the guidance of ELSI investigators and coordinated by the MAGen CC. ELSI research projects should build upon existing ELSI scholarship and should focus primarily on the use of ML/AI tools to be developed and validated by the Consortium, and secondarily on the use of ML/AI in genomic medicine more broadly. ELSI research projects designed during the UG3 Phase should be well integrated and relevant to the overall aims of the Consortium’s activities. Across the Consortium, ELSI research projects that build on existing scholarship should be planned. Topics may include but are not limited to the following:
   • The extent to which the Consortium is responsive to the established ELSI framework, given existing opportunities and constraints.
   • The extent to which the drafted ELSI framework influences or improves the tool development process.
   • ELSI issues associated with any limitations of ML/AI tool development and cross validation.
   • The perceptions of different potential users about the ML/AI tools, such as understandability, reliability, utility, or value.
   • Ways in which the ELSI framework might be improved for future use.
   • ELSI issues that may arise across relevant groups in the future use of ML/AI tools.
   • Strategies to mitigate potential harm and ensure appropriate benefit in the use of ML/AI tools with diverse populations.
     Projects may include but are not limited to applied research, ethnographic research, empirical qualitative and quantitative methods, and conceptual, legal, and normative analyses. Projects may use mixed methods (e.g., quantitative and qualitative research) and iterative processes (e.g., concurrent data collection and analysis, use of data in real-time, adapting study design based on findings). Engagement with communities in the general public and other interested groups who may be impacted by use of ML/AI tools is encouraged but not required. By the end of the UG3 Phase, each Site should have identified at least one ELSI research project for implementation during the UH3 Phase.
9. Dissemination of the Consortium Resources: Entails providing input to the MAGen CC-led development of a Consortium-wide plan for the dissemination of Consortium developed tools and resources and disseminating according to the plan. While the resources will be shared primarily in AnVIL, resources may also be shared in other community repositories, as appropriate. The plan must include specifications and protocols for the preparation of items prior to dissemination and a corresponding timeline. At a minimum, tools, resources, and products for dissemination must include, but are not limited to the following:
   • The ELSI framework used to guide ML/AI tool development and validation
   • Validated ML/AI tools, corresponding metadata for the intended use of these resources by the research community (1) version control; (2) methods to document and share training and validation experiments; (3) choice of model registries and model sharing platforms etc.
   • Common data model
   • Data preprocessing scripts as appropriate
   • Cross validation plan
   • Research findings
   • Best practices
   • Gaps in data, technologies, and policies which remain to be addressed.
      

Transition from UG3 to UH3 Phase

The transition from the UG3 to the UH3 phase is contingent upon the successful completion of milestones proposed for the UG3 phase. Milestones proposed in the application by the MAGen Sites may be revised and approved by the NHGRI during the UG3 and UH3 Phases to align with the Consortium-wide milestones.  Consortium-wide milestones are developed by the MAGen Sites and the MAGen CC and the NHGRI staff to enable coordinated development of the consortium-wide resources which is a key feature of the MAGen program.

Four months prior to the expiration of the UG3 award, recipients will need to submit the transition package, which will include the UG3 progress report delineating progress toward achieving UG3 milestones and activities with milestones proposed for the UH3 phase. This application will be administratively reviewed internally by NHGRI for consideration for the UH3 phase award. Thus, recipients of the UG3 awards should note that there is no guarantee of a subsequent UH3 award. Consideration for the UH3 award is contingent upon submission of this transition package and satisfactory progress towards the UG3 milestones.

The criteria to determine the transition to the UH3 Phase will be based on the satisfactory progress in meeting the milestones and deliverables. Such criteria include but are not limited:

• Drafting an ELSI Framework agreed upon by the Consortium that reflects ELSI issues relevant to a broad range of groups who may be impacted, directly or indirectly, by use of ML/AI tools.
• Identification of at least one ELSI Research Project for implementation by each Site during UH3 Phase.
• Identification of the Consortium-wide gene set for which ML/AI tools can be developed and cross validated.
• Development of the ML/AI tool requirements that can adequately address the clinical questions and engender trustworthiness in the results.
• Preparation of datasets that are adequate and appropriate to support ML/AI tool development and cross validation for the assigned genes.
• Development of a mature, comprehensive, and suitable data model to allow ML/AI tool development by the different MAGen Sites.
• Development of a cross validation plan that can feasibly address the robustness and generalizability of the ML/AI tools.

NHGRI may adopt additional consideration criteria for the Consortium’s transition from the UG3 to the UH3 phase.

In the event of an UH3 award, recipient PD/PIs and the NHGRI staff will negotiate the final list of milestones for the entire Consortium for each year of support. 

UH3 Phase – ML/AI Tool Development and Cross Validation and ESLI Research Projects Implementation (Years 3-5)

1. Developing ML/AI Tools: Entails development and testing of the ML/AI tools in accordance with the developed plans.
2. Cross Validating ML/AI Tools: Entails cross validation of the ML/AI tools in accordance with the developed plans. 
3. Implementing ELSI research projects: Entails finalization of the specific aims, study design, methods, personnel, timelines for ELSI research projects proposed during the UG3 Phase, carrying out planned research, and informing the ML/AI tool development and validation process and ELSI framework.  
4. Refining Consortium-Wide Plans: Entails periodically refinement of Consortium-wide plans for tool validation and cross-validation based on findings from the ELSI research projects, other ELSI scholarship, or insights gained during the consortium’s activities. This may involve establishing new agreed upon milestones to ensure timely completion of required activities by end of the UH3 Phase.
5. Implementing the Dissemination Plan: Entails preparing and disseminating the resources in accordance with the developed plans.

All applicants are strongly encouraged to contact the NHGRI Staff Contact for this NOFO to discuss the responsiveness and alignment of their proposed work with the goals of this program.

Non-Responsiveness to the NOFO

The following applications will be considered non-responsive to this NOFO and will result in the application being withdrawn prior to review:

• Applications that propose new primary data generation.
• Applications that do not propose a combined total of at least 4 candidate genes with pathogenic variants and associated human diseases for ML/AI tool development and cross validation. Among these genes, at least 2 genes should be proposed for development.
• Applications that do not propose the development of at least one tool for potential applications in genomic translational research, e.g. applications that solely develop in-silico variant effect predictors, generate a catalog of variant effects, elucidate gene function, biological pathways or networks.
• Applications that do not propose a plan for cross validation.
• Applications that do not propose at least one research project to explore ELSI issues related to the integration of ML/AI tools into potential genomic medicine applications.

Data sharing

Recipients are expected to collaborate with other members of the consortium and comply with the NIH Data Management and Sharing Policy (NOT-OD-21-013) and NIH Genomic Data Sharing Policy (NOT-OD-14-124). NHGRI supports the broadest appropriate data sharing with timely data release through widely accessible data repositories. Please follow the NIH guidance on writing a Data Management and Sharing (DMS) Plan here, and ensure the Plan is in alignment with NHGRI’s data sharing expectations, which are summarized at genome.gov/data-sharing.

Consortium Formation and Governance

This NOFO uses the Cooperative Agreement mechanism. Successful applicants will become members of the Consortium comprising investigators funded in response to either one of the two NOFOs: RFA-HG-24-004 and RFA-HG-24-005.

A Steering Committee (SC) will be the main governing body of the Consortium. The SC will be composed of the PD(s)/PI(s) from each Consortium’s award and NIH program staff. In addition to the PD(s)/PI(s), key personnel from each Site and working group representatives will be eligible to attend SC meetings. The SC will establish subcommittees or working groups to facilitate collaborative work and to achieve the Consortium’s goals. Major scientific decisions such as the ELSI Framework, identification of genes, variants, and datasets to be used for tool development, data model, tool requirements, cross validation plan, ELSI research projects, Consortium milestones etc., will be determined by consensus, and as needed, by majority vote of the SC, where each funded Site, the MAGen CC, and the NHGRI will each have a single vote. The SC will meet regularly and be assisted by the activities of working groups. 

An External Scientific Panel (ESP) of independent experts will provide input on performance, priorities, and overall progress of the consortium, including the administrative review of the Consortium’s accomplishments for the transition from the UG3 to UH3 phase. The ESP will consist of individuals with a broad range of expertise, including in multi-modal data, ML/AI tool development, software engineering, clinical research physicians, and ethicists/social scientists, and other areas as needed. The ESP will meet semi-annually (one conference call and one in-person meeting per year) in conjunction with SC meetings, as appropriate. Following each meeting, the ESP will generate recommendations for the SC to consider and respond to.

Informational Webinar and Frequently Asked Questions

An informational webinar will be held for potential applicants. During the webinar, NHGRI staff will present overviews of this NOFO RFA-HG-24-004 and its companion NOFO RFA-HG-24-005 and answer questions from prospective applicants. The informational webinar is open to all prospective applicants, but participation is not a prerequisite for submission of an application. Time, date, and dial in information will be posted at: https://www.genome.gov/event-calendar/MAGen-NOFO-Webinar .  A recording of the webinar will be posted on the above website, together with a list of Frequently Asked Questions from the applicants. 

See Section VIII. Other Information for award authorities and regulations.

Section II. Award Information

NIH grants policies as described in the NIH Grants Policy Statement will apply to the applications submitted and awards made from this NOFO.

Section III. Eligibility Information

1. Eligible Applicants

Higher Education Institutions

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

The following types of Higher Education Institutions are always encouraged to apply for NIH support as Public or Private Institutions of Higher Education:

• Hispanic-serving Institutions
• Historically Black Colleges and Universities (HBCUs)
• Tribally Controlled Colleges and Universities (TCCUs)
• Alaska Native and Native Hawaiian Serving Institutions
• Asian American Native American Pacific Islander Serving Institutions (AANAPISIs)

Nonprofits Other Than Institutions of Higher Education

• Nonprofits with 501(c)(3) IRS Status (Other than Institutions of Higher Education)
• Nonprofits without 501(c)(3) IRS Status (Other than Institutions of Higher Education)

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)

Federal Governments

• Eligible Agencies of the Federal Government
• U.S. Territory or Possession

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

Non-domestic (non-U.S.) Entities (Foreign Organizations) 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 allowed. 

Applicant Organizations

Applicant organizations must complete and maintain the following registrations as described in the How to Apply - 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. Failure to complete registrations in advance of a due date is not a valid reason for a late submission, please reference NIH Grants Policy Statement Section 2.3.9.2 Electronically Submitted Applications for additional information

• System for 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 which have not already been assigned a CAGE Code.
  • 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 on the grant application.
• eRA Commons - Once the unique organization identifier is established, organizations can register with eRA Commons in tandem with completing their Grants.gov registrations; all registrations must be in place by time of submission. eRA Commons requires organizations to identify at least one Signing Official (SO) and at least one Program Director/Principal Investigator (PD/PI) account in order to submit an application.
• Grants.gov – Applicants must have an active SAM registration in order to complete the Grants.gov registration.

Program Directors/Principal Investigators (PD(s)/PI(s))

All PD(s)/PI(s) must have an eRA Commons account.  PD(s)/PI(s) should work with their organizational officials to either create a new account or to affiliate their existing account with the applicant organization in eRA Commons. If the PD/PI is also the organizational Signing Official, they must have two distinct eRA Commons accounts, one for each role. Obtaining an eRA Commons account can take up to 2 weeks.

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 their organization to develop an application for support. Individuals from diverse backgrounds, including individuals from underrepresented racial and ethnic groups, individuals with disabilities, and women are always encouraged to apply for NIH support. See, Reminder: Notice of NIH's Encouragement of Applications Supporting Individuals from Underrepresented Ethnic and Racial Groups as well as Individuals with Disabilities, NOT-OD-22-019.

For institutions/organizations proposing multiple PDs/PIs, visit 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.

2. Cost Sharing

This NOFO does not require cost sharing as defined in the NIH Grants Policy Statement NIH Grants Policy Statement Section 1.2 Definition of Terms.

3. Additional Information on Eligibility

Number of Applications

Applicant organizations may submit more than one application, provided that each application is scientifically distinct.

The NIH will not accept duplicate or highly overlapping applications under review at the same time, per NIH Grants Policy Statement Section 2.3.7.4 Submission of Resubmission Application. This means that the NIH will not accept:

• A new (A0) application that is submitted before issuance of the summary statement from the review of an overlapping new (A0) or resubmission (A1) application.
• A resubmission (A1) application that is submitted before issuance of the summary statement from the review of the previous new (A0) application.
• An application that has substantial overlap with another application pending appeal of initial peer review (see NIH Grants Policy Statement 2.3.9.4 Similar, Essentially Identical, or Identical Applications).

Section IV. Application and Submission Information

1. Requesting an Application Package

The application forms package specific to this opportunity must be accessed through ASSIST, Grants.gov Workspace or an institutional system-to-system solution. Links to apply using ASSIST or Grants.gov Workspace are available in Part 1 of this NOFO. See your administrative office for instructions if you plan to use an institutional system-to-system solution.

2. Content and Form of Application Submission

It is critical that applicants follow the instructions in the Research (R) Instructions in the How to Apply - Application Guide except where instructed in this notice of funding opportunity to do otherwise. Conformance to the requirements in the How to Apply - Application Guide is required and strictly enforced. Applications that are out of compliance with these instructions may be delayed or not accepted for review.

Letter of Intent

Although a letter of intent is not required, is not binding, and does not enter into the review of a subsequent application, the information that it contains allows IC staff to estimate the potential review workload and plan the review.

By the date listed in Part 1. Overview Information, prospective applicants are asked to submit a letter of intent that includes the following information:

• Descriptive title of proposed activity
• Name(s), address(es), and telephone number(s) of the PD(s)/PI(s)
• Names of other key personnel
• Participating institution(s)
• Number and title of this funding opportunity

The letter of intent should be sent to:

Sandhya Xirasagar, Ph.D.
Telephone: 240-380-0400
Email: xirasasa@nih.gov

Page Limitations

All page limitations described in the How to Apply – Application Guide and the Table of Page Limits must be followed.

For this specific NOFO, the Research Strategy section is limited to 30 pages.

The following section supplements the instructions found in the How to Apply – Application Guide and should be used for preparing an application to this NOFO.

SF424(R&R) Cover

All instructions in the How to Apply - Application Guide must be followed.

SF424(R&R) Project/Performance Site Locations

All instructions in the How to Apply - Application Guide must be followed.

SF424(R&R) Other Project Information

All instructions in the How to Apply - Application Guide must be followed.

SF424(R&R) Senior/Key Person Profile

All instructions in the How to Apply - Application Guide must be followed.

R&R Budget

All instructions in the How to Apply - Application Guide must be followed.

Effective management of this development Site requires a significant commitment by the Program Director(s)/Principal Investigator(s) and Project Manager (PM). For an application proposing a single PD/PI, the PD/PI and PM are each expected to devote at least 2.4 person months annually to the project. If multi-PDs/PIs are proposed, the aggregate level of effort required is a minimum of 2.4 person months. In the MPI model, PDs/PIs should devote sufficient time to serve his/her proposed role while maintaining the aggregate minimum required level of effort.

All MAGen Sites are expected to participate in the Consortium’s collaborative activities including development/implementation of data model, ML/AI tool cross validation plans, ELSI Framework, dissemination plans, establishment of governance for the above activities etc., and should budget accordingly. Budgets should include costs for active Consortium participation, including regular teleconferences and meetings of the SC and its working groups. A virtual kick-off meeting will be held within 30 days of award.

One annual in-person (2 days, 1-2 nights) Consortium-wide meeting should be included in the budget for the UG3 and UH3 Phases. Budgets should include costs for twice monthly SC virtual meetings in the UG3 Phase, and monthly SC virtual meetings in the UH3 Phase and other virtual meetings as appropriate.

Costs for ELSI personnel and resources needed to design and develop the ELSI Framework and design and conduct the ELSI Research Projects should be included and estimated to be 10% of the costs for the entire budget.
Costs for cloud and other storage and computing resources should be included in the budget and fully justified. 
For budgeting purposes, each Site should assume it will be conducting tool development for 1 gene and cross-validation of 2-3 genes.

Budgets should include any funds required to support sharing of scientific data under this NOFO, as per guidance on allowable costs for data management and sharing on its Budgeting for Data Management & Sharing webpage.

R&R Subaward Budget

All instructions in the How to Apply - Application Guide must be followed.

PHS 398 Cover Page Supplement

All instructions in the How to Apply - Application Guide must be followed.

PHS 398 Research Plan

All instructions in the How to Apply - Application Guide must be followed, with the following additional instructions:

1. Overview:
Provide a high-level description of the proposed project (max 3 pages), including:

• Goals of the proposed project.
• How the proposed research approach will meet the goals of this NOFO.
• Significance and innovation of the proposed approach.

2. Personnel Skills and Experience

• Team’s multi-disciplinary expertise in ML/AI tool development from multi-modal data (including clinical, genomic, other omics, phenotypic, SDOH, ancestry, environmental exposure, etc.), high performance and cloud computing, data modeling and management, translational and clinical genomics research, computational genomics and data science, ELSI research, and other expertise.
• How the skills of individual team members will contribute to the collective capability to achieve the goals of the Consortium.
• Previous participation of the applicant’s team in past team science or large research networks.

3. Administrative Functions and Project Management, Collaboration and Coordination

• Describe the project management and organizational structure of the proposed Site, with roles and responsibilities of key personnel. Describe how the day-to-day activities of the Site will be coordinated within the project, with the other members of the Consortium, and NHGRI staff to achieve the proposed goals and milestones for both the UG3 and UH3 phases and resolve conflicts.
• Describe how guidance and recommendations from the ESP will be incorporated in the implementation of the proposed project.
• Describe staff recruitment efforts to meet the proposed timelines and milestones. Risk mitigation strategies to address challenges with staff recruitment should also be described.

4. Data Infrastructure and Computational Resources

Provide details of the data infrastructure and compute resources (e.g. number and types of nodes, tiers, time of usage, etc.,) that are anticipated to be needed to meet the goals of this NOFO. Estimate costs for data storage, compute, and egress.

5. ELSI Framework
Propose and provide the rationale for a process to draft a Framework or set of guiding ELSI principles to inform the activities of the Consortium. Specifically:

• Detail collaboration between ELSI and other investigators, within and across MAGen Sites.
• Explain how the process will be informed by and built upon existing ELSI scholarship and Frameworks.
• Explain how perspectives of various groups directly or indirectly impacted by the use of ML/AI tools will be assessed and incorporated.

Desirable characteristics of the draft Framework include but are not limited to well-defined and prioritized ELSI issues that can be pragmatically assessed or addressed in MAGen and a systematic approach to assessing the merits and implications of key decisions made by the Consortium.

6. Human Genes, Variants and DiseasesPropose, 2-4 genes for ML/AI tool development and 2-4 other genes for cross validation. This requires that:

• The proposed genes must have pathogenic variants associated with known human diseases and with variable clinical manifestation. The selected genes may be associated with one or more distinct disorders, for example proposing genes associated to only cardiomyopathy is acceptable, as is selecting genes that cause unrelated disorders. A few examples of genes that could meet these criteria include HFE, F5, BRCA1, BRCA2, TTR, TTN, LDLR, APOE, SCN5A, and KCNQ1.
• At least one of the genes proposed for tool development and one of the genes proposed for cross validation have pathogenic variants that are relatively common in the population to increase the likelihood that other MAGen Sites will have sufficient datasets to perform cross validation.

7. Datasets for ML/AI Tool Development
Describe the proposed datasets and reference knowledge to be used for ML/AI tool development, validation, and cross validation for the proposed genes.

• Provide verification of accessibility, for example, include evidence of approvals by data access committees, the Head of Research, the legal department and the Chief Information Officer, Chief Security Officer, etc.
• Describe the multimodal nature of the datasets, as well as the advantages and challenges of the use of such data for AI/ML tool development.
• Describe the approaches that will be used to make the proposed datasets ready for ML/AI tool development and validation, including a proposed data model, and how to address potential challenges such as sparsity of the data, heterogenous data sources, poorly documented metadata, biases in the sampled population.
• Explain whether and how these datasets can be made accessible to other MAGen Sites as necessary to investigate the source of any discrepancies that may arise during tool cross-validation.

8. ML/AI Tool Development
Provide the rationale for the proposed technologies and how they will be applied to develop ML/AI tools based on the proposed multimodal datasets. In particular, describe:

• The inputs and outputs of the ML/AI tools proposed to be developed.
• How the proposed tools may be applicable in translational genomic research settings and propose strategies to address ELSI concerns.
• The approach for ML/AI tool development to include training and validation. Describe the approach to selecting tools (reuse versus developing anew), qualitative and quantitative metrics that will be used to assess the accuracy and performance of the tools, which may include uncertainty quantification, trustworthiness, interpretability, and usability etc.
• The targeted users who will be validating and cross validating the tools.
• The plans for optimizing the tools for high performance or cloud computing platforms.
• How the tools could be cross validated by other MAGen Sites in the NHGRI AnVIL or in another proposed cloud computing platform to assess their robustness and generalizability and applicability in different genomic translational research settings.
• Plans for tools dissemination and facilitating adoption by translational genomic researchers.

9. ELSI Research Projects
Describe the study design and plans for finalizing the specific aims of the ELSI Research Projects, carrying out planned research, and informing the ML/AI tool development and cross-validation, including:

• The significance of the ELSI research questions to be addressed.
• A description of and the rationale for the proposed methods.
• The plans to use findings e.g. to inform the validation work or iterate upon the ELSI framework.
• The applicability of the ELSI research to the Consortium’s goals for translational genomic research.

10. Disseminating ML/AI tools and resources
Describe and provide the rationale for the approach for the dissemination of MAGen tools and resources. While the resources will be shared primarily in AnVIL, with adequate justification resources may also be shared in other community portals and tool registries. Tools, resources, and products for dissemination could include, but are not limited to, the following:

• The ELSI framework used to guide ML/AI tool development and validation,
• Validated ML/AI tools, corresponding metadata for the intended use of these tools by the research community, including (1) version control; (2) methods to document and share training and validation experiments; (3) choice of model registries and model sharing platforms etc.
• Common data model
• Data preprocessing scripts
• Cross validation plan
• Research findings
• Best practices
• Gaps in data, technologies, and policies which resulted in the inability to address some challenges

Resource Sharing Plan: Individuals are required to comply with the instructions for the Resource Sharing Plans as provided in the How to Apply - Application Guide.

• Resource Sharing Plans are expected for this NOFO.
• In the Resource Sharing Plan, applicants should indicate their willingness to abide by all software release standards and policies developed by the Consortium's SC and approved by NHGRI staff. Recipients are expected to develop such policies as members of the Consortium's SC in collaboration with NHGRI and should indicate their willingness to participate in the development of such policies and to accept them. These policies will remain consistent with NIH and NHGRI policies and resource sharing.

NHGRI is committed to the timely release of well-documented  open-source software and analyses including models and tools developed from proposed studies. Applicants should describe their plan for open dissemination of methods, protocols, software, and tools to the community such that they are readily usable and extensible, where applicable. Applicants should also propose plans for sharing their ML/AI model parameter specifications as appropriate and analytical protocols and methods.  Methods, protocols, tools, and software should be well-documented and where applicable made available via version-controlled public repositories including AnVIL as appropriate.

• Solutions that enhance reproducibility when used by the community and ability of the community to integrate into automated pipelines should be emphasized.
• In the Resource Sharing Plan, a plan for sharing software should describe how improvements or tool customizations will be managed and disseminated to the scientific community. Applicants should take responsibility for creating the original and subsequent official versions of a piece of software.

For a list of frequently asked questions about Best Practices for Sharing Research Software, see https://datascience.nih.gov/tools-and-analytics/best-practices-for-sharing-research-software-faq. 

Other Plan(s): Note: Effective for due dates on or after January 25, 2023, the Data Management and Sharing Plan will be attached in the Other Plan(s) attachment in FORMS-H application forms packages.

All instructions in the How to Apply - Application Guide must be followed, with the following additional instructions:

All applicants planning research (funded or conducted in whole or in part by NIH) that results in the generation of scientific data are required to comply with the instructions for the Data Management and Sharing Plan. All applications, regardless of the amount of direct costs requested for any one year, must address a Data Management and Sharing Plan.

NHGRI supports the broadest appropriate genomic, phenotypic, and metadata data sharing with timely data release through widely accessible data repositories. Per NOT-HG-21-022, NHGRI expects applications awarded under this NOFO to share comprehensive metadata and, where applicable, phenotypic data, use standardized data collection protocols and survey instruments for capturing data, as appropriate, and use standardized notation for metadata (e.g., controlled vocabularies or ontologies) to enable future data harmonization and secondary data analyses.

To ensure that maximal scientific benefit is derived from this significant public investment, this funding opportunity aims to advance and accelerate research by supporting rapid sharing of the resulting data with the broad scientific community for research use in the AnVIL platform as possible and appropriate, through submission of variant interpretations to ClinVar, and through publication in the scientific literature.

Appendix: Only limited Appendix materials are allowed. Follow all instructions for the Appendix as described in the How to Apply - Application Guide.

PHS Human Subjects and Clinical Trials Information

When involving human subjects research, clinical research, and/or NIH-defined clinical trials (and when applicable, clinical trials research experience) follow all instructions for the PHS Human Subjects and Clinical Trials Information form in the How to Apply - Application Guide, with the following additional instructions:

If you answered “Yes” to the question “Are Human Subjects Involved?” on the R&R Other Project Information form, you must include at least one human subjects study record using the Study Record: PHS Human Subjects and Clinical Trials Information form or Delayed Onset Study record.

Study Record: PHS Human Subjects and Clinical Trials Information

All instructions in the How to Apply - Application Guide must be followed.

Delayed Onset Study

Note: Delayed onset does NOT apply to a study that can be described but will not start immediately (i.e., delayed start). All instructions in the How to Apply - Application Guide must be followed.

PHS Assignment Request Form

All instructions in the How to Apply - Application Guide must be followed.

3. Unique Entity Identifier and System for Award Management (SAM)

See Part 2. Section III.1 for information regarding the requirement for obtaining a unique entity identifier and for completing and maintaining active registrations in System for Award Management (SAM), NATO Commercial and Government Entity (NCAGE) Code (if applicable), eRA Commons, and Grants.gov

4. Submission Dates and Times

Part I. contains information about Key Dates and times. Applicants are encouraged to submit applications before the due date to ensure they have time to make any application corrections that might be necessary for successful submission. When a submission date falls on a weekend or Federal holiday, the application deadline is automatically extended to the next business day.

Organizations must submit applications to Grants.gov (the online portal to find and apply for grants across all Federal agencies). Applicants must then complete the submission process by tracking the status of the application in the eRA Commons, NIH’s electronic system for grants administration. NIH and Grants.gov systems check the application against many of the application instructions upon submission. Errors must be corrected and a changed/corrected application must be submitted to Grants.gov on or before the application due date and time.  If a Changed/Corrected application is submitted after the deadline, the application will be considered late. Applications that miss the due date and time are subjected to the NIH Grants Policy Statement Section 2.3.9.2 Electronically Submitted Applications.

Applicants are responsible for viewing their application before the due date in the eRA Commons to ensure accurate and successful submission.

Information on the submission process and a definition of on-time submission are provided in the How to Apply – Application Guide.

5. Intergovernmental Review (E.O. 12372)

This initiative is not subject to intergovernmental review.

6. Funding Restrictions

All NIH awards are subject to the terms and conditions, cost principles, and other considerations described in the NIH Grants Policy Statement.

Pre-award costs are allowable only as described in the NIH Grants Policy Statement Section 7.9.1 Selected Items of Cost.

7. Other Submission Requirements and Information

Applications must be submitted electronically following the instructions described in the How to Apply - Application Guide. Paper applications will not be accepted.

Applicants must complete all required registrations before the application due date. Section III. Eligibility Information contains information about registration.

For assistance with your electronic application or for more information on the electronic submission process, visit How to Apply – Application Guide. If you encounter a system issue beyond your control that threatens your ability to complete the submission process on-time, you must follow the Dealing with System Issues guidance. For assistance with application submission, contact the Application Submission Contacts in Section VII.

Important reminders:

All PD(s)/PI(s) must include their eRA Commons ID in the Credential field of the Senior/Key Person Profile form. Failure to register in the Commons and to include a valid PD/PI Commons ID in the credential field will prevent the successful submission of an electronic application to NIH. See Section III of this NOFO for information on registration requirements.

The applicant organization must ensure that the unique entity identifier provided on the application is the same identifier used in the organization’s profile in the eRA Commons and for the System for Award Management. Additional information may be found in the How to Apply - Application Guide.

See more tips for avoiding common errors.

Upon receipt, applications will be evaluated for completeness and compliance with application instructions by the Center for Scientific Review and responsiveness by NHGRI, NIH. Applications that are incomplete, non-compliant and/or nonresponsive will not be reviewed.

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In order to expedite review, applicants are requested to notify the NHGRI Referral Office by email at troyerj@mail.nih.gov when the application has been submitted. Please include the FON and title, PD/PI name, and title of the application.

Post Submission Materials

Applicants are required to follow the instructions for post-submission materials, as described in the policy

Any instructions provided here are in addition to the instructions in the policy.

Section V. Application Review Information

1. Criteria

Only the review criteria described below will be considered in the review process.  Applications submitted to the NIH in support of the NIH mission are evaluated for scientific and technical merit through the NIH peer review system.

Reviewers will provide an overall impact score to reflect their assessment of the likelihood for the project to exert a sustained, powerful influence on the research field(s) involved, in consideration of the following review criteria and additional review criteria (as applicable for the project proposed).

Reviewers will consider each of the review criteria below in the determination of scientific merit and give a separate score for each. An application does not need to be strong in all categories to be judged likely to have major scientific impact. For example, a project that by its nature is not innovative may be essential to advance a field.

As applicable for the project proposed, reviewers will evaluate the following additional items while determining scientific and technical merit, and in providing an overall impact score, but will not give separate scores for these items.

As applicable for the project proposed, reviewers will consider each of the following items, but will not give scores for these items, and should not consider them in providing an overall impact score.

2. Review and Selection Process

Applications will be evaluated for scientific and technical merit by (an) appropriate Scientific Review Group(s) convened by the NHGRI Scientific Review Branch, in accordance with NIH peer review policies and practices, using the stated review criteria. Assignment to a Scientific Review Group will be shown in the eRA Commons.

As part of the scientific peer review, all applications will receive a written critique.

Applications may undergo a selection process in which only those applications deemed to have the highest scientific and technical merit (generally the top half of applications under review) will be discussed and assigned an overall impact score.

Appeals of initial peer review will not be accepted for applications submitted in response to this NOFO.

Applications will be assigned to the appropriate NIH Institute or Center. Applications will compete for available funds with all other recommended applications submitted in response to this NOFO. Following initial peer review, recommended applications will receive a second level of review by the National Advisory Council for Human Genome Research (NACHGR). The following will be considered in making funding decisions:

• Scientific and technical merit of the proposed project as determined by scientific peer review.
• Availability of funds.
• Relevance of the proposed project to program priorities.
• Potential for broader application or generalization.
• Programmatic balance, including synergy with other proposed Sites to collaboratively achieve the goals fo the NOFO.
• Potential to work effectively in collaborative efforts or research consortia, which may be based on previous experience with NIH-funded research consortia, if applicable.
• Synergy with other funded projects.
• Quality of plan for dissemination.
• Institutions that have not received substantial funding from NH in the past.
• Inclusion of new investigators and experienced investigators that are new to NHGRI consortia.

3. Anticipated Announcement and Award Dates

After the peer review of the application is completed, the PD/PI will be able to access his or her Summary Statement (written critique) via the eRA Commons. Refer to Part 1 for dates for peer review, advisory council review, and earliest start date.

Information regarding the disposition of applications is available in the NIH Grants Policy Statement Section 2.4.4 Disposition of Applications.

Section VI. Award Administration Information

1. Award Notices

If the application is under consideration for funding, NIH will request "just-in-time" information from the applicant as described in the NIH Grants Policy Statement. This request is not a Notice of Award nor should it be construed to be an indicator of possible funding. 

A formal notification in the form of a Notice of Award (NoA) will be provided to the applicant organization for successful applications. The NoA signed by the grants management officer is the authorizing document and will be sent via email to the recipient's business official.

Recipients must comply with any funding restrictions described in Section IV.6. Funding Restrictions. Selection of an application for award is not an authorization to begin performance. Any costs incurred before receipt of the NoA are at the recipient's risk. These costs may be reimbursed only to the extent considered allowable pre-award costs.

Any application awarded in response to this NOFO will be subject to terms and conditions found on the Award Conditions and Information for NIH Grants website.  This includes any recent legislation and policy applicable to awards that is highlighted on this website.

Institutional Review Board or Independent Ethics Committee Approval: Recipient institutions must ensure that protocols are reviewed by their IRB or IEC. To help ensure the safety of participants enrolled in NIH-funded studies, the recipient must provide NIH copies of documents related to all major changes in the status of ongoing protocols.

2. Administrative and National Policy Requirements

All NIH grant and cooperative agreement awards include the NIH Grants Policy Statement as part of the NoA. For these terms of award, see the NIH Grants Policy Statement Part II: Terms and Conditions of NIH Grant Awards, Subpart A: General and Part II: Terms and Conditions of NIH Grant Awards, Subpart B: Terms and Conditions for Specific Types of Grants, Recipients, and Activities, including of note, but not limited to:

• Federalwide Standard Terms and Conditions for Research Grants
• Prohibition on Certain Telecommunications and Video Surveillance Services or Equipment
• Acknowledgment of Federal Funding

If a recipient is successful and receives a Notice of Award, in accepting the award, the recipient agrees that any activities under the award are subject to all provisions currently in effect or implemented during the period of the award, other Department regulations and policies in effect at the time of the award, and applicable statutory provisions.

If a recipient receives an award, the recipient must follow all applicable nondiscrimination laws. The recipient agrees to this when registering in SAM.gov. The recipient must also submit an Assurance of Compliance (HHS-690). To learn more, see the Laws and Regulations Enforced by the HHS Office for Civil Rights website.

HHS recognizes that NIH research projects are often limited in scope for many reasons that are nondiscriminatory, such as the principal investigator’s scientific interest, funding limitations, recruitment requirements, and other considerations. Thus, criteria in research protocols that target or exclude certain populations are warranted where nondiscriminatory justifications establish that such criteria are appropriate with respect to the health or safety of the subjects, the scientific study design, or the purpose of the research. For additional guidance regarding how the provisions apply to NIH grant programs, please contact the Scientific/Research Contact that is identified in Section VII under Agency Contacts of this NOFO.

In accordance with the statutory provisions contained in Section 872 of the Duncan Hunter National Defense Authorization Act of Fiscal Year 2009 (Public Law 110-417), NIH awards will be subject to System for Award Management (SAM.gov) requirements. SAM.gov requires Federal agencies to review and consider information about an applicant in the designated integrity and performance system (currently SAM.gov) prior to making an award. An applicant can review and comment on any information in the responsibility/qualification records available in SAM.gov. NIH will consider any comments by the applicant, in addition to the information available in the responsibility/qualification records in SAM.gov, in making a judgement about the applicant’s integrity, business ethics, and record of performance under Federal awards when completing the review of risk posed by applicants as described in 2 CFR Part 200.206 “Federal awarding agency review of risk posed by applicants.” This provision will apply to all NIH grants and cooperative agreements except fellowships.

The following special terms of award are in addition to, and not in lieu of, otherwise applicable U.S. Office of Management and Budget (OMB) administrative guidelines, U.S. Department of Health and Human Services (HHS) grant administration regulations at 2 CFR Part 200, and other HHS, PHS, and NIH grant administration policies.

The administrative and funding instrument used for this program will be the cooperative agreement, an "assistance" mechanism (rather than an "acquisition" mechanism), in which substantial NIH programmatic involvement with the recipients is anticipated during the performance of the activities. Under the cooperative agreement, the NIH purpose is to support and stimulate the recipients' activities by involvement in and otherwise working jointly with the recipients in a partnership role; it is not to assume direction, prime responsibility, or a dominant role in the activities. Consistent with this concept, the dominant role and prime responsibility resides with the recipients for the project as a whole, although specific tasks and activities may be shared among the recipients and NIH as defined below.

The PD(s)/PI(s) will have the primary responsibility for:

• Determining research approaches, designing protocols, setting project milestones, and timelines and conducting research to meet the objectives of this NOFO.
• Leading, participating in, and contributing to the Consortium activities. 
• Adhering to the Consortium-established plans, processes, best practices, and SOPs.
• Implementing recommendations of the ESP
• Ensuring that the software, resources, materials, etc. are released appropriately according to the Resource Sharing Plan and the Consortium’s resources dissemination plan.
• Ensuring that the data generated under this project are released according to the NHGRI’s approved Data Management and Sharing Plan.
• Adhering to the guidelines and policies regarding data sharing, data access, and intellectual property established by the NIH, NHGRI, and the Steering Committee (SC) for the Consortium.
• Preparing abstracts, presentations, and publications in a timely manner.
• Not disclosing confidential information.
• Attending and participating in SC and other working group meetings, and implementing the decisions, guidelines, and procedures delineated by the SC, External Scientific Panel, and NHGRI, as appropriate.
• Interacting with other relevant NHGRI and NIH activities, as needed.
• In the event of no transition to the UH3 phase of the award, submitting a close-out plan within two (2) months of the award termination.  
• Recipient(s) will retain custody of and have primary rights to the data and software developed under these awards, subject to Government policies regarding rights of access consistent with current DHHS, PHS, and NIH policies.

NIH staff have substantial programmatic involvement that is above and beyond the normal stewardship role in awards, as described below:

The Project Scientist/Scientific Officer (PS/SO) at NHGRI is a dual role held by a NHGRI Program Director. The PS/SO will have substantial scientific and programmatic involvement during the conduct of this activity through technical assistance, advice, and coordination. The PS/SO will be responsible for the normal scientific and programmatic stewardship of the award. The role of NHGRI PS/SO will be to facilitate and not to direct the activities. It is anticipated that decisions in all activities will be reached by consensus of the Consortium’s members and NIH staff will offer input to this process.

This NOFO is a milestone-driven cooperative agreement program using the UG3/UH3 Cooperative Agreement mechanism involving NIH program staff in the negotiation of the final project plan before and during the award period, and monitoring of research progress. NHGRI’s funding for the MAGen Sites and the MAGen CC will be based on the satisfactory progress of the whole Consortium in meeting the Consortium’s milestones and deliverables.  The PS/SO will participate as a member of the SC and will have one vote. The PS/SO will be named in the Notice of Award and will have the following substantial involvement:

• Attending SC meetings as a voting member, and assisting in developing operating guidelines, quality control procedures, and consistent policies for dealing with situations that require coordinated action.
• Participating with SC members to set research priorities, decide optimal research approaches and protocol designs, and contribute to the adjustment of milestones and approaches as warranted. The PS/SO will assist and facilitate the committee’s process and not direct it.
• Serving as a liaison between the Consortium and NHGRI or NIH, recipient and as an information resource for the recipients about research activities. The PS/SO will also coordinate the efforts of the program with other groups conducting similar studies.
• Reporting periodically on the progress of the program to NHGRI’s leadership, and to the National Advisory Council for Human Genome Research.
• Serving as a liaison between the SC and the External Scientific Panel, attending External Scientific Panel meetings in a non-voting liaison member role, and arranging for timely preparation and distribution of the ESP’s meeting minutes.
• Serving on working groups of the SC and the External Scientific Panel, as appropriate.
• Providing advice in the management and technical performance of the award.
• Assisting in promoting the availability of the data, tools and other resources developed in the course of this program to the scientific community at large.
• Being responsible for the normal scientific and programmatic stewardship of the award, including monitoring and assessments of how well the recipient has met any milestones required for each year of funding.
• Curtailing, withholding, or reducing support for any recipient that fails to make satisfactory progress toward the work scope that NHGRI approved, has ethical or conflict of interest issues, or fails to comply with the Terms and Conditions of Award.

Where warranted and consistent with authorship and conflict of interest requirements of journals in which the Consortium decides to publish, participating in data analyses, interpretations, and co-authorship of the publication of Consortium results through their role in scientific program management.

Areas of Joint Responsibility include:

Close interaction among the participating Consortium member teams will be required, as well as significant involvement from the NIH, to develop appropriate strategies and tools to meet the goals of this NOFO. The recipients and the Project Scientist will meet regularly as the program SC.

The SC will be the main governing body of the Consortium. The SC will be composed of the PD(s)/PI(s) from each Consortium’s award and NIH program staff. In addition to the PD(s)/PI(s), key personnel from each Site and working group representatives will be eligible to attend SC meetings. The SC will establish subcommittees or working groups to facilitate collaborative work and to achieve the Consortium’s goals. Major scientific decisions such as the ELSI Framework, identification of genes, variants, and datasets to be used for tool development, data model, tool requirements, cross validation plan, ELSI research projects, Consortium milestones etc., will be determined by consensus, and as needed, by majority vote of the SC, where each funded Site, the MAGen CC, and the NHGRI will each have a single vote. The SC will meet regularly and be assisted by the activities of working groups.  

Dispute Resolution:

Any disagreements that may arise in scientific or programmatic matters (within the scope of the award) between recipients and NIH may be brought to Dispute Resolution. A Dispute Resolution Panel composed of three members will be convened: a designee of the SC chosen without NIH staff voting, one NIH designee, and a third designee with expertise in the relevant area who is chosen by the other two; in the case of individual disagreement, the first member may be chosen by the individual recipient. This special dispute resolution procedure does not alter the recipient's right to appeal an adverse action that is otherwise appealable in accordance with PHS regulation 42 CFR Part 50, Subpart D and HHS regulation 45 CFR Part 16.

3. Data Management and Sharing

Consistent with the 2023 NIH Policy for Data Management and Sharing, when data management and sharing is applicable to the award, recipients will be required to adhere to the Data Management and Sharing requirements as outlined in the NIH Grants Policy Statement. Upon the approval of a Data Management and Sharing Plan, it is required for recipients to implement the plan as described.

4. Reporting

When multiple years are involved, recipients will be required to submit the Research Performance Progress Report (RPPR) annually and financial statements as required in the NIH Grants Policy Statement.

A final RPPR, invention statement, and the expenditure data portion of the Federal Financial Report are required for closeout of an award, as described in the NIH Grants Policy Statement. NIH NOFOs outline intended research goals and objectives. Post award, NIH will review and measure performance based on the details and outcomes that are shared within the RPPR, as described at 2 CFR Part 200.301.

The Federal Funding Accountability and Transparency Act of 2006 as amended (FFATA), includes a requirement for recipients of Federal grants to report information about first-tier subawards and executive compensation under Federal assistance awards issued in FY2011 or later.  All recipients of applicable NIH grants and cooperative agreements are required to report to the Federal Subaward Reporting System (FSRS) available at www.fsrs.gov on all subawards over the threshold.  See the NIH Grants Policy Statement for additional information on this reporting requirement.

In accordance with the regulatory requirements provided at 2 CFR Part 200.113 and Appendix XII to 2 CFR Part 200, recipients that have currently active Federal grants, cooperative agreements, and procurement contracts from all Federal awarding agencies with a cumulative total value greater than $10,000,000 for any period of time during the period of performance of a Federal award, must report and maintain the currency of information reported in the System for Award Management (SAM) about civil, criminal, and administrative proceedings in connection with the award or performance of a Federal award that reached final disposition within the most recent five-year period.  The recipient must also make semiannual disclosures regarding such proceedings. Proceedings information will be made publicly available in the designated integrity and performance system (Responsibility/Qualification in SAM.gov, formerly FAPIIS).  This is a statutory requirement under section 872 of Public Law 110-417, as amended (41 U.S.C. 2313).  As required by section 3010 of Public Law 111-212, all information posted in the designated integrity and performance system on or after April 15, 2011, except past performance reviews required for Federal procurement contracts, will be publicly available.  Full reporting requirements and procedures are found in Appendix XII to 2 CFR Part 200 – Award Term and Condition for Recipient Integrity and Performance Matters.

Section VII. Agency Contacts

We encourage inquiries concerning this funding opportunity and welcome the opportunity to answer questions from potential applicants.

eRA Service Desk (Questions regarding ASSIST, eRA Commons, application errors and warnings, documenting system problems that threaten submission by the due date, and post-submission issues)

Finding Help Online: https://www.era.nih.gov/need-help (preferred method of contact)
Telephone: 301-402-7469 or 866-504-9552 (Toll Free)

General Grants Information (Questions regarding application instructions, application processes, and NIH grant resources)
Email: GrantsInfo@nih.gov (preferred method of contact)
Telephone: 301-637-3015

Grants.gov Customer Support (Questions regarding Grants.gov registration and Workspace)
Contact Center Telephone: 800-518-4726
Email: support@grants.gov

Jennie Larkin, Ph.D.
Division of Neuroscience (DN)
National Institute on Aging (NIA)
E-mail: jennie.larkin@nih.gov

Sandhya Xirasagar Ph.D.
National Human Genome Research Institute (NHGRI)
Telephone: 240-380-0400
Email: Xirasasa@nih.gov

Christine Cutillo
ODSS - Office of Data Science Strategy
Phone: none
E-mail: christine.cutillo@nih.gov

Rudy, Pozzatti, Ph.D.
National Human Genome Research Institute (NHGRI)
Telephone: 301-219-6235
Email: pozzattr@exchange.nih.gov

Jeni Smits
National Institute on Aging (NIA)
E-mail: jeni.smits@nih.gov

Lisa Oken
National Human Genome Research Institute (NHGRI)
Telephone: 301-594-5250
Email: Lisa.Oken@nih.gov

Section VIII. Other Information

Recently issued trans-NIH policy notices may affect your application submission. A full list of policy notices published by NIH is provided in the NIH Guide for Grants and Contracts. All awards are subject to the terms and conditions, cost principles, and other considerations described in the NIH Grants Policy Statement.

Awards are made under the authorization of Sections 301 and 405 of the Public Health Service Act as amended (42 USC 241 and 284) and under Federal Regulations 42 CFR Part 52 and 2 CFR Part 200.