Opportunity Information: Apply for PAR 16 277

  • 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 (R21)" 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.)
  • Each selected applicant is eligible to receive up to $200,000.00 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 (see text field entitled Additional Information on Eligibility for clarification).
Apply for PAR 16 277

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Opportunity Summary:

The Program to Assess the Rigor and Reproducibility of Exosome-Derived Analytes for Cancer Detection (R21) (Funding Opportunity Number PAR 16 277) is a National Institutes of Health (NIH) discretionary grant opportunity under HHS-NIH11 that supports exploratory, early-stage research aimed at improving how exosomes and their molecular contents are used for cancer detection. The core scientific goal is to advance reliable methods for isolating and characterizing exosomes and for analyzing the biological signals carried in exosome cargo, with a specific emphasis on identifying predictive biomarkers that could help with cancer risk assessment, early detection, diagnosis, and prognosis. In practical terms, the FOA is aimed at tackling a common bottleneck in the field: promising exosome-based signals often fail to translate because different labs use different isolation approaches, handle samples differently, apply inconsistent characterization standards, or rely on computational pipelines that are not fully reproducible across datasets and settings.

A major theme of this announcement is rigor and reproducibility. The FOA explicitly encourages projects that do more than simply discover potential biomarkers; it pushes applicants to design studies that test how robust exosome isolation and downstream analyses are when conditions change. That can include evaluating how different isolation techniques affect yield, purity, and the types of vesicles recovered, as well as how pre-analytical variables (like collection methods, storage conditions, processing time, or batch effects) influence the final readouts. On the computational side, the FOA highlights the need for reproducible analysis of exosomal cargo, meaning applicants are expected to pay attention to issues such as transparent and well-controlled bioinformatics workflows, repeatable feature selection, validation strategies that avoid overfitting, and approaches that can be replicated by other investigators using independent data. Overall, the program is framed around strengthening confidence that exosome-derived analytes can serve as dependable signals for early cancer-related decisions rather than fragile findings that depend on a single lab or a single analytic pipeline.

The opportunity uses the NIH R21 activity code, which is typically designed for exploratory or developmental research projects that can generate feasibility data, evaluate novel approaches, or establish initial proof-of-concept. The award ceiling listed for this FOA is $200,000. While the listing does not specify the expected number of awards, the structure and purpose indicate that the program is intended to seed innovation and methodological improvement in a rapidly evolving area, rather than fund large-scale clinical validation trials. The emphasis is on producing results, methods, and analytic practices that others can repeat and build on, which is especially important for biomarker discovery where reproducibility problems can derail translation into clinical tests.

Eligibility is broad and includes many types of organizations, reflecting NIH norms for research funding. Eligible applicants 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 and Indian housing authorities; nonprofit organizations (both with and without 501(c)(3) status); for-profit organizations other than small businesses; and small businesses. The funding activity category is listed under Education and Health, and the CFDA numbers associated with the opportunity are 93.394 (with another number also listed in the source data). The FOA was created and posted on May 23, 2016, with an original and current closing date of June 13, 2019.

Taken together, this FOA is best understood as an NIH effort to make exosome-based cancer biomarker research more trustworthy and more transferable. It encourages investigators to innovate in the lab methods used to obtain and verify exosomes, to carefully characterize what is being measured, and to build computational analyses of exosomal cargo that are transparent, testable, and reproducible. The intended outcome is a stronger methodological foundation for using exosome-derived analytes in early cancer detection and related clinical applications, reducing the gap between exciting preliminary signals and clinically reliable tests.

Frequently Asked Questions (FAQs)

What is the name of this grant opportunity?

The opportunity is titled Program to Assess the Rigor and Reproducibility of Exosome-Derived Analytes for Cancer Detection (R21).

What is the Funding Opportunity Number (FOA number)?

The Funding Opportunity Number is PAR 16 277.

Which agency is offering this grant?

This is a National Institutes of Health (NIH) discretionary grant opportunity under HHS-NIH11.

What type of NIH award mechanism is used?

The FOA uses the NIH R21 activity code, which is typically intended for exploratory and developmental research (early-stage studies, feasibility work, and proof-of-concept efforts).

What is the main purpose of this program?

The program supports exploratory, early-stage research aimed at improving how exosomes and their molecular contents (cargo) are used for cancer detection. A central aim is to strengthen the field by improving rigor and reproducibility in exosome isolation, characterization, and downstream analysis.

What scientific problem is this FOA trying to address?

The FOA targets a common bottleneck in exosome biomarker research: promising signals often fail to translate because labs may use different isolation approaches, sample handling procedures, characterization standards, or computational pipelines that do not reproduce well across datasets and settings.

What types of outcomes is this program trying to improve?

The focus is on building a stronger methodological foundation so exosome-derived analytes can become more dependable for cancer-related use cases such as risk assessment, early detection, diagnosis, and prognosis.

Is this FOA focused only on discovering new biomarkers?

No. While identifying predictive biomarkers is a stated emphasis, the FOA explicitly encourages projects that go beyond discovery by testing whether methods and signals remain robust when conditions change. The theme is reproducibility rather than one-off findings.

What does the FOA mean by “rigor and reproducibility” in practical terms?

The FOA highlights the need to design studies that evaluate whether exosome isolation and downstream analyses produce consistent, repeatable results. This includes both laboratory workflows and computational/bioinformatics workflows that other investigators can replicate.

What laboratory (wet-lab) topics does the FOA emphasize?

The FOA emphasizes advancing reliable methods to isolate and characterize exosomes and to analyze the biological signals in exosome cargo. It also encourages evaluating how different isolation techniques affect yield, purity, and the types of vesicles recovered.

What kinds of pre-analytical variables are highlighted?

The FOA specifically notes that pre-analytical variables can influence final readouts, including collection methods, storage conditions, processing time, and batch effects.

What computational or bioinformatics issues does the FOA call out?

On the computational side, the FOA stresses reproducible analysis of exosomal cargo, including attention to transparent and well-controlled workflows, repeatable feature selection, validation strategies that avoid overfitting, and approaches that can be replicated using independent data.

Why is reproducibility emphasized for exosome-derived analytes?

The FOA is framed around increasing confidence that exosome-derived analytes can serve as dependable signals for early cancer-related decisions, rather than fragile findings that only work in one lab or within one analytic pipeline.

What is the award ceiling for this FOA?

The listed award ceiling for this FOA is $200,000.

Does the FOA specify the expected number of awards?

The provided information does not specify the expected number of awards.

Is this opportunity intended to fund large-scale clinical validation trials?

Based on the structure and purpose described, the program is intended to seed innovation and methodological improvement rather than fund large-scale clinical validation trials.

Who is eligible to apply?

Eligibility is broad and includes many organization types, including:

  • 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
  • Nonprofit organizations with 501(c)(3) status
  • Nonprofit organizations without 501(c)(3) status
  • For-profit organizations other than small businesses
  • Small businesses

What is the funding activity category for this opportunity?

The funding activity category is listed under Education and Health.

What CFDA number(s) are associated with this opportunity?

The CFDA number listed is 93.394, and the source data also notes that another number is listed (without specifying it here).

When was the FOA created and posted?

The FOA was created and posted on May 23, 2016.

What are the closing dates for the FOA?

The original closing date and the current closing date are both listed as June 13, 2019.

What is the intended “big picture” impact of this program?

The program is intended to make exosome-based cancer biomarker research more trustworthy and transferable by improving lab methods, strengthening characterization practices, and promoting transparent, testable, reproducible computational analyses that others can repeat and build on.

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