Opportunity Information: Apply for RFA AT 24 008
Leveraging Data at Scale to Understand Natural Product Impacts on Whole Person Health (R01 Clinical Trial Not Allowed) is an NIH funding opportunity (RFA-AT-24-008) that supports research projects focused on building, adapting, or applying computational approaches to better understand how botanicals and other natural products may influence human biology in the context of whole person health. The core emphasis is on data-driven discovery: applicants are expected to bring together multiple distinct (orthogonal) chemical and/or biological datasets related to natural products and analyze them in ways that can produce new, testable hypotheses about biological activity, mechanisms, or broader health relevance. The opportunity is explicitly not for clinical trials, so the work is geared toward computational, informatics, and integrative analyses rather than interventional human studies.
A key requirement is true data integration at scale. Projects must leverage and merge multiple compatible or interoperable data sources and/or data types, rather than relying on a single dataset. In practice, this could include integrating chemical characterization data (for example, constituent profiles, metabolomics, or structural annotations) with biological readouts (such as gene expression, pathway activity, bioassay results, microbiome-related measures, or other omics and systems biology data). The goal is to use these combined views to generate insights that would not be reachable from one dataset alone, and to move toward hypotheses that can be validated in future experimental work (even if the validation itself is outside the scope of this particular award).
The NOFO encourages the use of artificial intelligence and machine learning methods, reflecting the expectation that applicants may need modern computational techniques to harmonize heterogeneous datasets, resolve inconsistencies, infer relationships, and identify patterns across large-scale data. Competitive projects are likely to emphasize robust computational tool development or adaptation, reproducible analytical workflows, and clear plans for how the integrated analyses will yield biologically meaningful, testable predictions about natural products in whole person health contexts. While tool development is supported, the intent is not tooling for its own sake; the computational work should be clearly connected to hypothesis generation about biological activity and health-relevant mechanisms.
This funding opportunity sits within the Consortium Advancing Research on Botanicals and Other Natural Products (CARBON) Program. CARBON is structured as a broader ecosystem of complementary efforts, and the NOFO notes additional program components, including the Botanical Dietary Supplements Translational Research Teams (RM1) mechanism and a Limited Competition Research Resource for Natural Product Nuclear Magnetic Resonance Data (R24). Taken together, this framing signals that the R01 projects are meant to contribute to a larger coordinated push to strengthen natural product research infrastructure, data resources, and translationally useful understanding, particularly by improving how disparate datasets can be combined and interpreted.
From an administrative standpoint, the award mechanism is an R01 research project grant under the NIH, categorized under health-related research funding activity. The original application due date listed is June 28, 2024, and the award ceiling is $500,000. The opportunity is open to a broad range of eligible applicants spanning public and private institutions of higher education, federal agencies, state and local governments, tribal governments and organizations, nonprofits (including both 501(c)(3) and non-501(c)(3) entities), for-profit organizations (other than small businesses), and small businesses. The eligibility list also explicitly highlights a variety of mission-driven and community-anchored organizations and institutions, including HBCUs, Hispanic-serving institutions, tribally controlled colleges and universities, Alaska Native and Native Hawaiian serving institutions, AANAPISI institutions, faith-based or community-based organizations, non-U.S. entities (foreign organizations), and U.S. territories or possessions. This broad eligibility suggests an interest in drawing on diverse expertise and perspectives across computational science, natural products chemistry, biology, and whole person health research.
Overall, the opportunity funds computationally focused R01 projects that can integrate multiple natural product-related chemical and biological datasets, apply scalable analytics (including AI/ML where appropriate), and produce clear, testable hypotheses about how natural products may affect biological systems and whole person health, while aligning with the larger CARBON program goals and explicitly excluding clinical trial activity.Apply for RFA AT 24 008
- The National Institutes of Health in the health sector is offering a public funding opportunity titled "Leveraging Data at Scale to Understand Natural Product Impacts on Whole Person Health (R01 Clinical Trial Not Allowed)" and is now available to receive applicants.
- Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 93.213, 93.321.
- This funding opportunity was created on 2024-03-05.
- Applicants must submit their applications by 2024-06-28. (Agency may still review applications by suitable applicants for the remaining/unused allocated funding in 2026.)
- Each selected applicant is eligible to receive up to $500,000.00 in funding.
- Eligible applicants include: State governments, County governments, City or township governments, Special district governments, Independent school districts, Public and State controlled institutions of higher education, Native American tribal governments (Federally recognized), Public housing authorities/Indian housing authorities, Native American tribal organizations (other than Federally recognized tribal governments), Nonprofits having a 501 (c) (3) status with the IRS, other than institutions of higher education, Nonprofits that do not have a 501 (c) (3) status with the IRS, other than institutions of higher education, Private institutions of higher education, For-profit organizations other than small businesses, Small businesses, Others.
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FAQs: Leveraging Data at Scale to Understand Natural Product Impacts on Whole Person Health (R01 Clinical Trial Not Allowed) - RFA-AT-24-008
What is this NIH funding opportunity?
This is an NIH R01 funding opportunity (RFA-AT-24-008) titled "Leveraging Data at Scale to Understand Natural Product Impacts on Whole Person Health (R01 Clinical Trial Not Allowed)." It supports research projects that build, adapt, or apply computational approaches to better understand how botanicals and other natural products may influence human biology in the context of whole person health.
What is the main focus of the funded research?
The core emphasis is data-driven discovery through large-scale integration and analysis of multiple distinct (orthogonal) chemical and/or biological datasets related to natural products. The expected outcome is new, testable hypotheses about biological activity, mechanisms, or broader health relevance that would not be reachable from analyzing a single dataset alone.
Are clinical trials allowed under this opportunity?
No. The opportunity is explicitly "Clinical Trial Not Allowed," meaning the work is geared toward computational, informatics, and integrative analyses rather than interventional human studies.
What kinds of projects are a good fit?
Projects are a good fit if they (1) integrate multiple compatible or interoperable natural product-related datasets at scale, (2) apply computational approaches (including AI/ML when appropriate) to harmonize and analyze those data, and (3) generate biologically meaningful, testable hypotheses about how botanicals or other natural products affect biological systems and whole person health.
What does "data integration at scale" mean in this NOFO?
It means combining and leveraging multiple data sources and/or data types in a true integrative way, not relying on a single dataset. The intent is to merge heterogeneous but compatible datasets so that joint analysis can reveal insights that cannot be obtained from any one dataset alone.
Do applicants need to use more than one dataset?
Yes. A key requirement is integration of multiple distinct (orthogonal) chemical and/or biological datasets. Proposals centered on only one dataset would not align with the stated emphasis on true integration.
What are examples of chemical datasets that could be integrated?
Examples mentioned include chemical characterization data such as constituent profiles, metabolomics, and structural annotations related to botanicals and other natural products.
What are examples of biological datasets that could be integrated?
Examples mentioned include gene expression data, pathway activity data, bioassay results, microbiome-related measures, and other omics and systems biology data.
Is the goal to prove health benefits directly within this R01?
The stated goal is to produce new, testable hypotheses about biological activity, mechanisms, or broader health relevance through integrated computational analyses. The NOFO points toward hypotheses that can be validated in future experimental work, even if validation itself is outside the scope of this particular award.
Is tool development supported?
Yes. The opportunity supports robust computational tool development or adaptation and reproducible analytical workflows, especially when these are necessary to harmonize heterogeneous datasets and perform integrative analyses.
Is building tools by itself enough to be competitive?
No. While tool development is supported, the intent is not tooling for its own sake. The computational work should be clearly connected to generating testable hypotheses about biological activity and health-relevant mechanisms related to natural products.
Does the NOFO encourage using artificial intelligence or machine learning?
Yes. The NOFO encourages AI/ML methods, reflecting the expectation that modern computational techniques may be needed to harmonize heterogeneous datasets, resolve inconsistencies, infer relationships, and identify patterns across large-scale data.
What kinds of outputs are expected from funded projects?
Expected outputs include integrated analyses that yield biologically meaningful and testable predictions or hypotheses about natural products, including insights into biological activity, mechanisms, and relevance to whole person health contexts.
How does this opportunity relate to the CARBON Program?
This NOFO sits within the Consortium Advancing Research on Botanicals and Other Natural Products (CARBON) Program. It is positioned as part of a broader ecosystem intended to strengthen natural product research infrastructure, data resources, and translationally useful understanding, particularly by improving how disparate datasets can be combined and interpreted.
Are there other CARBON-related components mentioned?
Yes. The NOFO notes additional CARBON program components including the Botanical Dietary Supplements Translational Research Teams (RM1) mechanism and a Limited Competition Research Resource for Natural Product Nuclear Magnetic Resonance Data (R24).
What is the funding mechanism?
The award mechanism is an NIH R01 research project grant, categorized under health-related research funding activity.
What is the application due date listed for this opportunity?
The original application due date listed is June 28, 2024.
What is the award ceiling?
The award ceiling listed for this opportunity is $500,000.
Who is eligible to apply?
The opportunity is open to a broad range of eligible applicants, including public and private institutions of higher education, federal agencies, state and local governments, tribal governments and organizations, nonprofits (including 501(c)(3) and non-501(c)(3) entities), for-profit organizations (other than small businesses), and small businesses.
Are mission-driven and community-anchored institutions included in eligibility?
Yes. The eligibility list explicitly highlights institutions and organizations such as HBCUs, Hispanic-serving institutions, tribally controlled colleges and universities, Alaska Native and Native Hawaiian serving institutions, AANAPISI institutions, and faith-based or community-based organizations.
Are non-U.S. entities eligible?
Yes. The eligibility list explicitly includes non-U.S. entities (foreign organizations), as well as U.S. territories or possessions.
What scientific areas does this opportunity bring together?
Based on the description, the opportunity is designed to draw on diverse expertise across computational science, informatics, natural products chemistry, biology, and whole person health research.
What is meant by "whole person health" in the context of this NOFO?
In this NOFO, whole person health is the context in which biological impacts of botanicals and other natural products are studied. The focus is on computational and integrative analyses that connect chemical and biological data to generate hypotheses about how natural products may influence human biology with broader health relevance.
Can a project focus only on chemical characterization or only on biological readouts?
The emphasis is on integrating multiple distinct datasets and producing insights not possible from one dataset alone. The NOFO examples point toward combining chemical characterization with biological readouts, suggesting that projects limited to a single data type would not meet the central integration expectation.
What makes an analysis "integrative" under this opportunity?
An integrative analysis, as described, involves harmonizing and merging multiple interoperable datasets and using computational approaches to infer relationships and patterns across them, ultimately producing new, testable hypotheses about biological activity and mechanisms relevant to health.
Does this opportunity fund experimental validation work?
The description emphasizes computational hypothesis generation and notes that hypotheses may be validated in future experimental work, even if validation is outside the scope of this award. No additional experimental scope is specified in the provided information.
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