Opportunity Information: Apply for PAR 18 844
The National Institutes of Health (NIH) funding opportunity titled "Investigator Initiated Research in Computational Genomics and Data Science (R01 Clinical Trial Not Allowed)" (Funding Opportunity Number: PAR-18-844) supports investigator-driven research that advances computational methods for genomics and genomic medicine. The focus is on research in computational genomics, data science, statistics, and bioinformatics that can strengthen either basic genomic science, clinical genomic science, or both, with clear relevance to improving understanding of human health and disease. The central idea is to fund work that enables progress across genomics broadly, rather than solutions tied to a single disease area or a narrowly defined biological system.
This opportunity is designed to back fundamental, methodologically innovative genomics research. That includes creating new analytical methodologies and computational approaches, developing early-stage tools and software, and improving existing tools through refinement, hardening, and increased robustness so they become reliable resources for the wider biomedical genomics community. In practical terms, NIH is looking for proposals that either introduce new computational capabilities or make high-value genomic software more usable, scalable, and dependable in real research environments. The expectation is that funded outputs will have broad utility, meaning they should generalize across multiple diseases, cohorts, and biological contexts rather than being custom-built for one dataset or one narrow use case.
A major emphasis in the announcement is scale. Applications are expected to explain how the proposed methods, pipelines, or software will handle increasingly large and complex datasets over time. This reflects the reality that genomics is moving toward larger population-scale sequencing efforts, richer multi-omics measurements, and growing integration of genomic data with clinical and phenotypic information. Competitive projects under this FOA typically make credible claims about computational efficiency, memory and storage considerations, and the ability to perform well as data volume, dimensionality, and heterogeneity expand. In other words, it is not enough for a method to work on a modest dataset; applicants need to demonstrate a thoughtful plan for scalability as genomics continues to grow.
The award mechanism is an NIH R01 research project grant, and the announcement explicitly states that clinical trials are not allowed under this FOA. That restriction generally means the funded work should not involve prospective assignment of human participants to an intervention to evaluate health-related outcomes. The emphasis is instead on computational and methodological research that can be broadly enabling, including tool-building and data-analysis innovations, which may still use existing human data resources when appropriate but without conducting a clinical trial.
From the provided source details, the opportunity is categorized as a discretionary grant in the health activity area under CFDA 93.172, administered by the NIH. The listing indicates eligibility for small businesses, which suggests that small business entities were among the eligible applicant types for this announcement as captured in the source data. The original closing date listed is 2021-09-07, and an award ceiling of $500,000 is provided in the summary information. The FOA was created on 2018-06-28. While the excerpt does not specify an expected number of awards, the intent is clearly to support a range of investigator-initiated projects that push forward computational genomics capabilities for the broader research community.
Overall, this funding opportunity is best understood as support for reusable, scalable computational innovations in genomics and data science: new statistical or machine-learning approaches for genomic inference, improved algorithms for analyzing sequencing or multi-omics data, tools that make genomic analyses more efficient and reproducible, and software engineering work that turns valuable but fragile research code into stable, widely usable tools. The projects NIH wants to fund here are those that can become foundational building blocks for the field and remain useful as datasets continue to expand in size and complexity.Apply for PAR 18 844
- The National Institutes of Health in the health sector is offering a public funding opportunity titled "Investigator Initiated Research in Computational Genomics and Data Science (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): 93.172.
- This funding opportunity was created on 2018-06-28.
- Applicants must submit their applications by 2021-09-07. (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: Small businesses.
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Frequently Asked Questions (FAQs)
What is the name of this NIH funding opportunity?
The opportunity is titled "Investigator Initiated Research in Computational Genomics and Data Science (R01 Clinical Trial Not Allowed)."
What is the Funding Opportunity Number (FOA number)?
The Funding Opportunity Number is PAR-18-844.
What type of grant mechanism is used for this opportunity?
This opportunity uses the NIH R01 research project grant mechanism.
Are clinical trials allowed under this FOA?
No. The announcement explicitly states "Clinical Trial Not Allowed," meaning projects should not include prospective assignment of human participants to an intervention to evaluate health-related outcomes.
What is the main purpose of this grant?
The goal is to support investigator-driven research that advances computational methods for genomics and genomic medicine, with clear relevance to improving understanding of human health and disease.
What research areas does NIH emphasize in this opportunity?
The FOA focuses on computational genomics, data science, statistics, and bioinformatics that strengthen basic genomic science, clinical genomic science, or both.
Does the FOA encourage work that is broadly useful across genomics?
Yes. The central intent is to fund enabling methods and tools that generalize broadly across genomics, rather than solutions tied to a single disease area or a narrowly defined biological system.
Is disease-specific research the primary focus here?
No. The emphasis is on work that enables progress across genomics broadly, rather than being custom-built for one dataset, one cohort, one disease, or a narrow biological context.
What kinds of project outputs are encouraged?
Examples described in the opportunity include new analytical methodologies and computational approaches, early-stage tools and software, and improvements to existing tools through refinement, hardening, and increased robustness so they become reliable resources for the wider biomedical genomics community.
Does this FOA support software development and tool-building?
Yes. NIH is looking for proposals that introduce new computational capabilities and/or make high-value genomic software more usable, scalable, and dependable in real research environments.
What does "methodologically innovative" mean in the context of this FOA?
Based on the description, it refers to fundamental, enabling advances such as new analytical methods, new computational approaches, and substantial improvements that make tools robust and reliable for broad community use.
How important is scalability in the review expectations described?
Scalability is a major emphasis. Applications are expected to explain how proposed methods, pipelines, or software will handle increasingly large and complex datasets over time.
What kinds of scaling challenges should applicants address?
The description highlights the need for credible plans around computational efficiency, memory and storage considerations, and performance as data volume, dimensionality, and heterogeneity expand.
Why does the FOA place so much emphasis on scale?
The rationale given is that genomics is moving toward larger population-scale sequencing efforts, richer multi-omics measurements, and growing integration of genomic data with clinical and phenotypic information.
Can projects use human genomic data?
The opportunity emphasizes computational and methodological research and notes that projects may still use existing human data resources when appropriate, but they must not conduct a clinical trial.
What is the activity area and CFDA listing mentioned for this opportunity?
The opportunity is categorized as a discretionary grant in the health activity area under CFDA 93.172, administered by the National Institutes of Health (NIH).
Who administers this funding opportunity?
It is administered by the National Institutes of Health (NIH).
Are small businesses eligible to apply?
Yes. The source details indicate eligibility for small businesses, suggesting small business entities are among the eligible applicant types for this announcement as captured in the source data.
What is the award ceiling listed in the summary information?
The summary information provides an award ceiling of $500,000.
When was this FOA created?
The FOA was created on 2018-06-28.
What is the original closing date listed for this opportunity?
The original closing date listed is 2021-09-07.
Does the provided excerpt state how many awards NIH expects to make?
No. The excerpt does not specify an expected number of awards.
What kinds of methods and approaches fit the scope described?
The description points to reusable, scalable computational innovations in genomics and data science, including new statistical or machine-learning approaches for genomic inference, improved algorithms for analyzing sequencing or multi-omics data, tools that make genomic analyses more efficient and reproducible, and software engineering work that turns fragile research code into stable, widely usable tools.
What does NIH mean by tools being "reliable resources" for the community?
Based on the description, NIH values refinement, hardening, and robustness improvements so tools become dependable and usable in real research environments by the wider biomedical genomics community.
What is the overarching theme of the projects NIH wants to fund through this FOA?
The overarching theme is foundational, broadly enabling computational genomics methods and software that remain useful as datasets continue to expand in size and complexity.
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