Opportunity Information: Apply for PAR 16 276
Apply for PAR 16 276
- The HHS-NIH11 in the education, health sector is offering a public funding opportunity titled "Program to Assess the Rigor and Reproducibility of Exosome-Derived Analytes for Cancer Detection (R01)" and is now available to receive applicants.
- Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 93.394,.
- This funding opportunity was created on May 23, 2016 and posted on May 23, 2016.
- Applicants must submit their applications by Jun 13, 2019. (Agency may still review applications by suitable applicants for the remaining/unused allocated funding in 2026.)
- 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 (see text field entitled Additional Information on Eligibility for clarification).
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Opportunity Summary:
The Program to Assess the Rigor and Reproducibility of Exosome-Derived Analytes for Cancer Detection (R01) (Funding Opportunity Number PAR 16 276) is a National Institutes of Health (NIH) research grant opportunity under the U.S. Department of Health and Human Services, focused on strengthening the scientific foundations behind using exosomes and their contents as biomarkers for early cancer detection. Exosomes are small extracellular vesicles released by cells that carry molecular cargo such as proteins, lipids, DNA, and multiple forms of RNA. Because tumors can shed exosomes into blood and other body fluids, exosome-derived analytes have attracted major interest as minimally invasive or noninvasive markers that might help identify cancer earlier, assess risk, support diagnosis, or predict prognosis. The central aim of this FOA is not simply to find new biomarkers, but to make sure that the methods used to isolate exosomes and analyze their cargo produce results that are reliable, comparable across labs, and reproducible over time.
A key emphasis of the announcement is rigor and reproducibility in two major parts of the exosome biomarker pipeline. First, it encourages innovative, carefully controlled research on exosome isolation and characterization. In practice, this means evaluating and improving how exosomes are separated from complex biological samples (for example, plasma, serum, urine, saliva, cerebrospinal fluid, or other biospecimens), and how researchers confirm that what they have isolated truly represents exosomes rather than a mix of vesicles, protein aggregates, lipoproteins, or other contaminants. Projects responsive to this goal typically address questions like how pre-analytical variables (sample collection, anticoagulant choice, storage temperature, freeze-thaw cycles, processing time, centrifugation protocols) affect yield and purity, and how different isolation technologies (ultracentrifugation, size-exclusion chromatography, precipitation, immunoaffinity capture, microfluidic methods, or hybrid workflows) compare when judged against standardized performance metrics. The FOA is positioned to support work that identifies sources of variability and bias, defines quality control benchmarks, and helps establish best practices so that independent groups can reproduce findings rather than generating results that only hold under narrow conditions.
Second, the FOA highlights rigor and reproducibility in computational analysis of exosomal cargo. Exosome studies often generate high-dimensional data, such as sequencing-based profiles of RNA species, proteomic signatures, or multi-omics panels, and these analyses can be highly sensitive to bioinformatics choices. This opportunity therefore supports research aimed at making computational pipelines more transparent, validated, and consistent, including steps such as normalization, batch-effect correction, feature selection, model training, cross-validation, and external validation. It is geared toward projects that can show how analytic decisions influence biomarker performance claims, reduce overfitting and false discovery, and improve the likelihood that proposed exosome-based signatures will replicate in independent cohorts, across different platforms, and in real-world sample conditions. In a cancer detection context, this kind of work is essential because a biomarker that looks impressive in one dataset can fail when moved to another lab or a broader patient population unless the underlying methodology is robust.
From an applicant and administrative standpoint, this is an R01 mechanism, meaning it supports investigator-initiated research projects of substantial scope and is intended for well-justified, hypothesis-driven or methodological studies with clearly defined aims and a strong plan for evaluation. The funding instrument is listed as a discretionary grant, and the activity category is Health (and also tagged under Education, Health in the source data). The Catalog of Federal Domestic Assistance (CFDA) numbers associated with the opportunity are 93.394 (and another listed as 93.394 in the source excerpt), reflecting NIH program cataloging. The sponsoring agency is identified as HHS-NIH11. The opportunity was posted and created on May 23, 2016, and the closing date shown in the source data is June 13, 2019 (both original and current closing dates match), indicating the final submission window in that listing. The award ceiling and expected number of awards are not specified in the provided source fields, so applicants would typically need to consult the full FOA text and NIH institute guidance for budgeting expectations, allowable costs, and any institute-specific paylines or constraints.
Eligibility is broad and includes a wide range of organizations that can contribute to this kind of translational and methods-focused research. Eligible applicants listed include state, county, and city or township governments; special district governments; independent school districts; public and state-controlled institutions of higher education; private institutions of higher education; federally recognized Native American tribal governments and other tribal organizations; public housing authorities/Indian housing authorities; nonprofits with and without 501(c)(3) status (excluding higher education institutions in those nonprofit categories as stated); for-profit organizations other than small businesses; small businesses; and other entities as clarified by additional eligibility text in the full announcement. This breadth reflects the interdisciplinary nature of exosome biomarker work, which often spans clinical oncology, molecular biology, analytical chemistry, bioengineering, and data science, and can be advanced by academic labs, clinical centers, and industry groups with specialized platforms.
Overall, the opportunity is best understood as an NIH-driven push to make exosome-based cancer biomarker research more dependable and comparable, addressing a common problem in the field: promising early findings that do not replicate because of inconsistent sample handling, isolation impurities, incomplete vesicle characterization, or unstable computational approaches. By supporting systematic studies that quantify variability, establish quality controls, and validate analytic pipelines, the program aims to improve the chances that exosome-derived analytes can move from exploratory discovery into credible, clinically meaningful tools for early cancer risk assessment, detection, diagnosis, and prognosis.
Frequently Asked Questions (FAQs)
What is the name of this funding opportunity?
The opportunity is titled Program to Assess the Rigor and Reproducibility of Exosome-Derived Analytes for Cancer Detection (R01).
What is the Funding Opportunity Number (FON)?
The Funding Opportunity Number is PAR 16 276.
Which agency is offering this grant?
This is a National Institutes of Health (NIH) grant opportunity under the U.S. Department of Health and Human Services (HHS). The sponsoring agency is identified as HHS-NIH11.
What type of grant mechanism is this?
This opportunity uses the R01 mechanism, which supports investigator-initiated research projects of substantial scope with well-justified aims and a strong evaluation plan.
What is the main purpose of this FOA?
The central purpose is to strengthen rigor and reproducibility in research that uses exosomes and exosome-derived analytes as biomarkers for early cancer detection. The focus is on making methods and results more reliable, comparable across laboratories, and reproducible over time.
Is this FOA mainly about discovering new cancer biomarkers?
No. While biomarker-related work is part of the context, the FOA emphasizes validating and improving the methods used to isolate exosomes and analyze their cargo so that findings are dependable and replicate across labs and studies.
What are exosomes (as described in the opportunity)?
Exosomes are small extracellular vesicles released by cells. They carry molecular cargo that can include proteins, lipids, DNA, and multiple forms of RNA.
Why are exosomes relevant to cancer detection?
Tumors can shed exosomes into blood and other body fluids, making exosome-derived analytes attractive as minimally invasive or noninvasive markers that could help with earlier identification of cancer, risk assessment, diagnosis support, or prognosis prediction.
What are the two major areas of emphasis for rigor and reproducibility?
The FOA emphasizes rigor and reproducibility in (1) exosome isolation and characterization and (2) computational analysis of exosomal cargo.
What kinds of research topics fit under exosome isolation and characterization?
Responsive projects can evaluate and improve how exosomes are separated from complex samples and how researchers confirm that the isolated material represents exosomes rather than contaminants (such as other vesicles, protein aggregates, or lipoproteins). The FOA highlights identifying sources of variability and bias, defining quality control benchmarks, and establishing best practices.
Which biospecimens are specifically mentioned as examples?
Examples include plasma, serum, urine, saliva, cerebrospinal fluid, and other biospecimens.
What pre-analytical variables does the FOA highlight as important?
The FOA calls attention to factors such as sample collection methods, anticoagulant choice, storage temperature, freeze-thaw cycles, processing time, and centrifugation protocols, because these can affect exosome yield, purity, and downstream results.
What exosome isolation technologies are mentioned?
Examples listed include ultracentrifugation, size-exclusion chromatography, precipitation, immunoaffinity capture, microfluidic methods, and hybrid workflows.
What does the FOA mean by verifying that isolated material is truly exosomes?
It refers to careful exosome characterization to distinguish exosomes from potential contaminants (for example, other vesicles, protein aggregates, or lipoproteins) and to support comparable and reproducible results across studies.
What is the computational analysis focus of this opportunity?
The FOA supports work to make computational pipelines for exosomal cargo analysis more transparent, validated, and consistent, especially when handling high-dimensional data that can be sensitive to bioinformatics choices.
What kinds of data are mentioned as examples of "high-dimensional" exosome data?
The FOA mentions data such as sequencing-based profiles of RNA species, proteomic signatures, and multi-omics panels.
Which computational pipeline steps are specifically called out?
Examples include normalization, batch-effect correction, feature selection, model training, cross-validation, and external validation.
Why does the FOA emphasize avoiding overfitting and false discoveries?
Because a biomarker signature can appear strong in one dataset but fail in another setting. The FOA aims to improve the likelihood that exosome-based signatures replicate in independent cohorts, across different platforms, and under real-world sample conditions.
What is the funding instrument and activity category?
The funding instrument is a discretionary grant. The activity category is listed as Health (and also tagged under Education, Health in the source data).
What CFDA number(s) are associated with this opportunity?
The CFDA number provided is 93.394 (listed in the source excerpt as 93.394, including a duplicate listing).
When was this opportunity posted and created?
The posting and creation date shown is May 23, 2016.
What is the closing date shown in the provided information?
The closing date shown is June 13, 2019, and the original and current closing dates match in the provided listing.
Is the award ceiling specified?
No. The award ceiling is not specified in the provided source fields.
Is the expected number of awards specified?
No. The expected number of awards is not specified in the provided source fields.
Where should applicants look for budgeting expectations and allowable costs?
Based on the provided information, applicants would typically need to consult the full FOA text and relevant NIH institute guidance for budgeting expectations, allowable costs, and any institute-specific constraints.
Who is eligible to apply?
Eligibility is broad. Eligible applicants listed include:
- State governments
- County governments
- City or township governments
- Special district governments
- Independent school districts
- Public and state-controlled institutions of higher education
- Private institutions of higher education
- Federally recognized Native American tribal governments
- Other Native American tribal organizations
- Public housing authorities / Indian housing authorities
- Nonprofits with 501(c)(3) status (excluding higher education institutions in that nonprofit category as stated)
- Nonprofits without 501(c)(3) status (excluding higher education institutions in that nonprofit category as stated)
- For-profit organizations other than small businesses
- Small businesses
- Other entities as clarified by additional eligibility text in the full announcement
Why is eligibility so broad for this program?
The FOA reflects the interdisciplinary nature of exosome biomarker work, which can involve clinical oncology, molecular biology, analytical chemistry, bioengineering, and data science, and can be advanced by academic, clinical, government, nonprofit, and industry organizations.
What types of research outcomes does this FOA aim to encourage?
The FOA aims to support systematic studies that quantify variability, establish quality controls, and validate analytic pipelines, improving the credibility and comparability of exosome-derived analytes for cancer risk assessment, detection, diagnosis, and prognosis.
What common problem in the field is this FOA trying to address?
The opportunity targets the issue of promising findings that fail to replicate due to inconsistent sample handling, isolation impurities, incomplete vesicle characterization, or unstable computational approaches.
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Applicants also applied for:
Applicants who have applied for this opportunity (PAR 16 276) also looked into and applied for these:
| Funding Opportunity |
|---|
| Fogarty HIV Research Training Program for Low-and Middle-Income Country Institutions (D43) Apply for PAR 16 279 Funding Number: PAR 16 279 Agency: HHS-NIH11 Category: Education, Health Funding Amount: $280,000 |
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| Planning Grant for Fogarty HIV Research Training Program for Low-and Middle-Income Country Institutions (D71) Apply for PAR 16 281 Funding Number: PAR 16 281 Agency: HHS-NIH11 Category: Education, Health Funding Amount: $28,000 |
| Program to Assess the Rigor and Reproducibility of Exosome-Derived Analytes for Cancer Detection (R21) Apply for PAR 16 277 Funding Number: PAR 16 277 Agency: HHS-NIH11 Category: Education, Health Funding Amount: $200,000 |
| Cancer Prevention, Control, Behavioral Sciences, and Population Sciences Career Development Award (K07) Apply for PAR 16 284 Funding Number: PAR 16 284 Agency: HHS-NIH11 Category: Education, Health Funding Amount: Case Dependent |
| Silencing of HIV-1 Proviruses (R61/R33) Apply for RFA AI 16 038 Funding Number: RFA AI 16 038 Agency: HHS-NIH11 Category: Education, Health Funding Amount: $500,000 |
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| Linking the Provider Recommendation to Adolescent HPV Vaccine Uptake (R03) Apply for PAR 16 337 Funding Number: PAR 16 337 Agency: HHS-NIH11 Category: Education, Health Funding Amount: $50,000 |
| Linking the Provider Recommendation to Adolescent HPV Vaccine Uptake (R21) Apply for PAR 16 336 Funding Number: PAR 16 336 Agency: HHS-NIH11 Category: Education, Health Funding Amount: $200,000 |
| Linking the Provider Recommendation to Adolescent HPV Vaccine Uptake (R01) Apply for PAR 16 338 Funding Number: PAR 16 338 Agency: HHS-NIH11 Category: Education, Health Funding Amount: Case Dependent |
| U.S.-Russia Bilateral Collaborative Research Partnerships (CRP) on the Prevention and Treatment of HIV/AIDS and HIV-Associated Comorbidities (R01) Apply for RFA AA 17 006 Funding Number: RFA AA 17 006 Agency: Department of Health and Human Services, National Institutes of Health Category: Education, Health Funding Amount: $200,000 |
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