Key Dates

Related Announcements

• October 9, 2020 - Administrative Supplements to Existing NIH Grants and Cooperative Agreements (Parent Admin Supp Clinical Trial Optional). See NOFO PA-20-272.

Issued by

National Institute of General Medical Sciences (NIGMS)

Purpose

The National Institute of General Medical Sciences (NIGMS) announces the availability of funds for administrative supplements to NIGMS-funded awardees to build cloud-based learning modules for biomedical research.

Background

Biomedical research is increasingly dependent on access to and analysis of large and complex datasets. Cloud computing enables efficient data analysis and management without investment in on-premises high-performance computing infrastructure and maintenance by individual institutions. To realize the potential of cloud computing  in expanding access to cutting-edge data and data analysis capacity, the biomedical research workforce needs effective learning and research tools to obtain hands-on experience with cloud computing. Faculty-built cloud learning modules allow both the trainer (faculty) and the trainees (students and researchers) to become adept at using cloud computing for biomedical research. This “train the trainer” process is efficiently accomplished through the NIGMS Sandbox.

The NIGMS Sandbox is a GitHub repository of NIGMS investigator-built, cloud-based, self-learning modules for diverse biomedical data science topic areas that were developed with prior NIGMS funding (NOT-GM-22-004). These modules have detailed instructions and 508-compliant videos for launching the modules on a cloud platform, conducting data analyses, and drawing inferences to study various biological mechanisms. This NOSI seeks to expand the NIGMS Sandbox repository by developing new modules that can be incorporated into curricula, workshops, and training. 

Research Objectives

This administrative supplement supports faculty investigators to work with cloud software engineers supported by the NIH to develop cloud-based biomedical data science training modules for topics including, but not limited to, the following:

• Protein structure and dynamics, including structure prediction, structure-based drug discovery and protein-protein interactions
• Metabolomic and interactome mapping
• Analysis of genetic variants, genome-wide association studies, population genetics, and quantitative trait analysis
• Phylogeny and evolution
• Microbiome, virome, and ecology of host-microbe interactions 
• Data analysis, simulation, and modeling of complex biological systems

These modules should complement and have minimal overlap with the existing NIGMS Sandbox modules. The modules should be appropriate for integration into undergraduate or graduate curricula and for self-learning by researchers who are new to a field. Applicants are encouraged to consult with the Scientific Contact listed below to discuss the suitability of their proposed modules. The learning modules should include elements such as instructional videos, interactive demonstrations, and practicum exercises that encourage and enable self-learning. Use of innovative, active learning approaches is encouraged. Through each module, individuals are expected to learn a specific data analysis approach and develop expertise in interfacing with the cloud platform in a cost-effective manner.

Faculty investigators who serve as the project leads are expected to be familiar with computational technologies, including software programming. They will work with cloud software engineers provided by NIGMS/NIH STRIDES and be trained through a “train-the-trainer” engagement while developing the learning modules.

Applicants do not need to propose or describe the technical specifics of converting research training materials into cloud-based learning modules. They must be committed to making the learning modules broadly accessible to students and researchers through the NIGMS Sandbox. Applicants are also encouraged to propose innovative ways to incorporate the learning modules into their ongoing research training activities (courses, workshops, etc.).

Eligibility

Applicants for this supplement must have an active IDeA Networks for Biomedical Research Excellence (INBRE), Native American Research Centers for Health (NARCH) award, or an NIGMS institutional training (T34, T32) or research education (R25) award that supports undergraduate, graduate student, or postdoctoral trainees. Project leads who have not previously received training for developing NIGMS Sandbox learning modules are encouraged to apply. Applications that substantially overlap with existing learning modules in the NIGMS Sandbox will be a low priority for funding.

Only one supplement request per parent award listed above will be accepted. The parent award must be active when the supplement application is submitted (e.g., within the originally reviewed and approved project period), regardless of the time remaining on the current project. The project must not constitute a change in scope of the parent award.

Application and Submission Information

Applications for this initiative must be submitted using the following opportunity or its subsequent reissuance.

• PA-20-272 - Administrative Supplements to Existing NIH Grants and Cooperative Agreements (Parent Admin Supp Clinical Trial Optional)

All instructions in the SF424 (R&R) Application Guide and PA-20-272 must be followed, with the following additions:

• Application Due Date – February 15, 2024, by 5:00 PM local time of applicant organization.
• For funding consideration, applicants must include “NOT-GM-24-006” (without quotation marks) in the Agency Routing Identifier field (box 4B) of the SF424 R&R form. Applications without this information in box 4B will not be considered for this initiative.
• Budget:
  • The requested length of award may not exceed one year.
  • Applications may request a budget for up to 6 person-months of salary support for the project leads and up to 2 person-months for student effort to test the modules. NIGMS will pay for and coordinate the train-the-trainer process required for the project.
  • Applicants should note that the funds from this supplement cannot be used to support trainee stipends or tuition or participant costs (e.g., for R25, T32, or T34 institutional research education or training grants).
  • For T32 and T34 awardees, application budgets should be for costs in Training Related Expenses.
  • As part of the budget justification, include a brief statement regarding currently available unobligated grant funds, as well as expenditure plans to demonstrate the need for additional funds. 
  • Supplements may provide support above the established dollar limit for the parent grant award.
• The Research Strategy section of the application is limited to 6 pages and should include the following:
  • Background and significance of the proposed learning module, including an outline of the teaching material, a description of how it can be used for research training, and a plan for assessing its effectiveness.
  • Technical design documentation that describes the process flow, software packages, data inputs, and data outputs. The training input datasets should be publicly available and use published methods of analysis that are widely accepted in the community.
  • A description of the learning objectives and key features of the learning module. A brief review of the availability of existing cloud-based learning tools on the same or similar subjects to the proposed teaching material is expected. Differences between the proposed module and what is currently available in the NIGMS Sandbox must be highlighted.
  • A description of the project lead’s technical expertise with computational technologies including software programming.
  • A dissemination plan to provide students broad access to the learning module, such as inclusion in the course curriculum, summer training, and workshops. Applicants should also affirm their commitment to disseminate their modules through the NIGMS Sandbox. 
  • A plan with a commitment to complete building the learning module in one year.

Review Information

Applications will be evaluated for scientific and technical merit by an appropriate internal review panel convened by NIGMS using the following criteria:

• Is the module complementary to, and not overlapping with, the existing modules within the NIGMS Sandbox?
• Is the module addressing a clear need in biomedical research training?
•  Is the module appropriate for the target audience?
• Are the learning objectives appropriate and is the module likely to achieve them?
• Does the project lead(s) have the technical expertise appropriate to work effectively with cloud engineers?
• Is there an effective dissemination plan to make the learning module accessible to the broad research community and to incorporate the learning module into the project lead’s teaching activities?
• Are the timelines and milestones well-defined and feasible?
• Are the costs allowable and fully justified?

Applicants are strongly encouraged to notify the contact listed below that a request has been submitted in response to this NOSI to facilitate efficient processing of the request.

Inquiries

Please direct all inquiries to:

Lakshmi Kumar Matukumalli, Ph.D.
National Institute of General Medical Sciences (NIGMS)
Email: lakshmi.matukumalli@nih.gov