Opportunity Information: Apply for PA 10 025
Apply for PA 10 025
- The National Institutes of Health in the education health sector is offering a public funding opportunity titled "Development, Application, and Evaluation of Prediction Models for Cancer Risk and Prognosis (R01)" and is now available to receive applicants.
- Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 93.393 Cancer Cause and Prevention Research 93.394 Cancer Detection and Diagnosis Research 93.395 Cancer Treatment Research 93.399 Cancer Control.
- This funding opportunity was created on Nov 16, 2009 and posted on Nov 16, 2009.
- Applicants must submit their applications by Jan 7, 2013. (Agency may still review applications by suitable applicants for the remaining/unused allocated funding in 2026.)
- Eligible applicants include: County governments For profit organizations other than small businesses Native American tribal governments (Federally recognized) Private institutions of higher education State governments City or township governments Nonprofits that do not have a 501(c)(3) status with the IRS, other than institutions of higher education Small businesses Public and State controlled institutions of higher education 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 Others (see text field entitled Additional Information on Eligibility for clarification) Independent school districts Special district governments.
- Other Eligible Applicants include the following Eligible Agencies of the Federal Government Indian/Native American Tribal Governments (Other than Federally Recognized) Non domestic (non U.S.) Entities (Foreign Organizations) U.S. Territory or Possession.
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Opportunity Summary:
The National Cancer Institute (NCI) grant opportunity titled "Development, Application, and Evaluation of Prediction Models for Cancer Risk and Prognosis (R01)" (Funding Opportunity Number PA-10-025) supports research aimed at improving how cancer risk and outcomes are predicted. The core idea is to move beyond single-factor or narrowly built tools and fund projects that either strengthen existing prediction models or create new ones, using data that already exist in clinical systems, cohorts, registries, biobanks, and other research and health data sources. NCI is looking for work that makes prediction models more accurate, more generalizable, and more usable in real research and clinical settings, ultimately benefiting researchers, clinicians, and even members of the public who rely on understandable and actionable risk information.
This FOA is especially aimed at investigators who live at the intersection of clinical care and population science, including clinicians, epidemiologists, geneticists, statisticians, and translational researchers working in cancer control and prevention. NCI emphasizes that strong applications will treat prediction modeling as a full pipeline: not just building a model, but also applying it to relevant questions, validating it rigorously, and testing whether it actually adds value in practice. In other words, the expectation is not only methodological novelty, but also proof that the model performs well and can be implemented or interpreted in ways that meaningfully improve decision-making.
Two major challenges in prediction modeling are highlighted as central motivations for this funding. The first is integrating diverse data types into coherent, usable models. NCI explicitly calls out the need to combine information such as clinical variables, demographics, pathology, environmental exposures, epidemiologic measures, outcomes, and genetic data, often stored across separate data warehouses or "data marts" that were never designed to work together. The second challenge is strong validation. The FOA signals that it is not enough for a model to work in the dataset where it was developed; investigators are expected to validate models in multiple independent populations and report real-world performance metrics such as sensitivity, specificity, and positive and negative predictive values. This emphasis reflects a practical concern: many published models look promising initially but fail when tested in new settings, different patient populations, or different health systems.
The FOA is not intended to fund basic discovery of new biomarkers or marker characterization efforts by themselves. Applications focused primarily on finding or describing prognostic or diagnostic markers, without a clear prediction modeling and validation framework, are considered out of scope. The focus stays on prediction models and their performance, transportability, and utility rather than on marker discovery as the main endpoint.
Funding is provided through the NIH R01 research project grant mechanism, which is generally used for more mature, multi-year research programs with substantial scope. This announcement runs in parallel with a companion opportunity of the same scientific scope under the R21 exploratory/developmental mechanism (PA-10-026), which is typically used for earlier-stage, higher-risk ideas or pilot work. Awards under PA-10-025 depend on the availability of funds and the number of high-quality applications received, meaning there is no guaranteed number of awards and the competition depends on overall applicant strength in a given cycle.
In terms of eligibility, the FOA is broadly open to a wide range of applicant organizations. Eligible applicants include public and private institutions of higher education, nonprofit and for-profit organizations (including small businesses), state and local governments (including counties, cities, townships, special districts, and independent school districts), federally recognized tribal governments and other tribal organizations, U.S. territories and possessions, and even certain non-U.S. entities (foreign organizations). Federal agencies are also included among eligible applicants under the additional eligibility language. There is no cost-sharing or matching requirement, which reduces barriers for applicants that may not have discretionary funds to meet a match.
Administratively, the opportunity was posted and created on November 16, 2009, with an original and current closing date of January 7, 2013, and an archive date of February 7, 2013. The sponsoring agency is the National Institutes of Health, with the program housed at NCI and encouraged by both the Division of Cancer Control and Population Sciences (DCCPS) and the Division of Cancer Treatment and Diagnosis (DCTD). The activity aligns with multiple CFDA numbers covering cancer cause and prevention research (93.393), detection and diagnosis (93.394), treatment research (93.395), and cancer control (93.399), underscoring that prediction modeling can span prevention through treatment and survivorship, as long as the central deliverable is a validated, useful risk or prognostic prediction tool.
For full details, applicants were directed to the NIH Grants Guide posting (http://grants.nih.gov/grants/guide/pa-files/PA-10-025.html). Technical access issues were routed to the NIH Office of Extramural Research (OER) webmaster contacts listed in the announcement.
Frequently Asked Questions (FAQs)
What is the name of this grant opportunity?
The opportunity is titled "Development, Application, and Evaluation of Prediction Models for Cancer Risk and Prognosis (R01)."
What is the Funding Opportunity Number (FOA number)?
The Funding Opportunity Number is PA-10-025.
Which agency is sponsoring this opportunity?
The sponsoring agency is the National Institutes of Health (NIH), with the program housed at the National Cancer Institute (NCI).
Which parts of NCI are encouraging applications?
The announcement notes encouragement from the Division of Cancer Control and Population Sciences (DCCPS) and the Division of Cancer Treatment and Diagnosis (DCTD).
What is the main purpose of this FOA?
The purpose is to support research that improves prediction of cancer risk and prognosis by developing new prediction models or strengthening existing ones, using existing data sources and demonstrating that models are accurate, generalizable, and usable in real research and clinical settings.
What kinds of research does NCI want to fund under this FOA?
NCI is looking for projects that treat prediction modeling as a full pipeline: developing or improving models, applying them to relevant questions, validating them rigorously in independent populations, and evaluating whether they add value in practice. The emphasis is on performance, transportability, and practical utility.
Is this FOA focused on cancer risk models, prognosis models, or both?
Both. The FOA covers prediction models for cancer risk as well as prediction models for cancer prognosis (outcomes).
Does this FOA emphasize single-factor predictors or broader models?
It emphasizes moving beyond single-factor or narrowly built tools, supporting models that combine multiple factors and perform reliably across settings.
What data sources are expected to be used?
The FOA highlights using data that already exist in clinical systems, cohorts, registries, biobanks, and other research and health data sources.
What kinds of data elements does NCI expect investigators to integrate?
The FOA explicitly calls out integrating diverse data types, such as clinical variables, demographics, pathology, environmental exposures, epidemiologic measures, outcomes, and genetic data.
Why does the FOA emphasize integrating diverse data types?
One central motivation described is that relevant information is often spread across separate data warehouses or "data marts" that were not designed to work together, and there is a need to combine these inputs into coherent, usable prediction models.
How important is validation in this FOA?
Validation is a major emphasis. The FOA signals that it is not sufficient for a model to work only in the dataset where it was developed; applicants are expected to validate models in multiple independent populations and report real-world performance.
What performance metrics does the FOA mention for model evaluation?
The FOA specifically mentions sensitivity, specificity, and positive and negative predictive values as examples of real-world performance metrics to report.
Does the FOA require models to be generalizable?
Yes. A key goal is to make models more generalizable (transportable) so they perform well across different populations, settings, or health systems.
Who is this funding opportunity especially aimed at?
It is especially aimed at investigators at the intersection of clinical care and population science, including clinicians, epidemiologists, geneticists, statisticians, and translational researchers working in cancer control and prevention.
Is methodological novelty enough to be competitive?
The FOA indicates that strong applications should include more than methodological novelty; they should also provide proof that the model performs well and can be implemented or interpreted in ways that meaningfully improve decision-making.
Is basic biomarker discovery an appropriate focus for this FOA?
No. The FOA is not intended to fund basic discovery of new biomarkers or marker characterization efforts by themselves.
What happens if an application focuses primarily on identifying or describing diagnostic or prognostic markers?
Applications focused mainly on finding or describing markers, without a clear prediction modeling and validation framework, are described as out of scope.
What grant mechanism is used for this opportunity?
Funding is provided through the NIH R01 research project grant mechanism, which is generally used for more mature, multi-year research programs with substantial scope.
Is there a companion funding opportunity for earlier-stage or pilot work?
Yes. A companion opportunity with the same scientific scope is available under the R21 exploratory/developmental mechanism (PA-10-026), which is described as being used for earlier-stage, higher-risk ideas or pilot work.
Are awards guaranteed under this FOA?
No. Awards depend on the availability of funds and the number of high-quality applications received, and the number of awards is not guaranteed.
Who is eligible to apply?
Eligibility is broad and includes public and private institutions of higher education; nonprofit and for-profit organizations (including small businesses); state and local governments (including counties, cities, townships, special districts, and independent school districts); federally recognized tribal governments and other tribal organizations; U.S. territories and possessions; and certain non-U.S. entities (foreign organizations). Federal agencies are also included under the additional eligibility language.
Are for-profit organizations eligible?
Yes. For-profit organizations, including small businesses, are listed among eligible applicants.
Are non-U.S. (foreign) organizations eligible?
Yes. The eligibility description includes certain non-U.S. entities (foreign organizations).
Are tribal governments and tribal organizations eligible?
Yes. Federally recognized tribal governments and other tribal organizations are included among eligible applicants.
Are state and local governments eligible?
Yes. State and local governments are eligible, including counties, cities, townships, special districts, and independent school districts.
Is there a cost-sharing or matching requirement?
No. The FOA states there is no cost-sharing or matching requirement.
When was this opportunity posted?
The opportunity was posted and created on November 16, 2009.
What were the closing and archive dates?
The original and current closing date listed is January 7, 2013, and the archive date is February 7, 2013.
Which CFDA program areas are associated with this FOA?
The FOA aligns with multiple CFDA numbers: 93.393 (cancer cause and prevention research), 93.394 (detection and diagnosis), 93.395 (treatment research), and 93.399 (cancer control).
Does the FOA allow prediction modeling work across the cancer continuum?
Yes. The CFDA alignment underscores that prediction modeling can span prevention through treatment and survivorship, as long as the central deliverable is a validated, useful risk or prognostic prediction tool.
Where were applicants directed for full details?
Applicants were directed to the NIH Grants Guide posting at http://grants.nih.gov/grants/guide/pa-files/PA-10-025.html.
Where were technical access issues routed?
Technical access issues were routed to the NIH Office of Extramural Research (OER) webmaster contacts listed in the announcement.
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Applicants also applied for:
Applicants who have applied for this opportunity (PA 10 025) also looked into and applied for these:
| Funding Opportunity |
|---|
| Development, Application, and Evaluation of Prediction Models for Cancer Risk and Prognosis (R21) Apply for PA 10 026 Funding Number: PA 10 026 Agency: National Institutes of Health Category: Education Health Funding Amount: $200,000 |
| Development and Application of PET and SPECT Imaging Ligands as Biomarkers for Drug Discovery and for Pathophysiological Studies of CNS Disorders (Phased Innovation Award R21/R33) Apply for PAR 10 024 Funding Number: PAR 10 024 Agency: National Institutes of Health Category: Education Health Funding Amount: Case Dependent |
| Development and Application of PET and SPECT Imaging Ligands as Biomarkers for Drug Discovery and for Pathophysiological Studies of CNS Disorders (R21) Apply for PA 10 023 Funding Number: PA 10 023 Agency: National Institutes of Health Category: Education Health Funding Amount: $200,000 |
| Epigenetic Approaches in Cancer Epidemiology (R01) Apply for PA 10 031 Funding Number: PA 10 031 Agency: National Institutes of Health Category: Education Health Funding Amount: Case Dependent |
| Epigenetic Approaches in Cancer Epidemiology (R21) Apply for PA 10 032 Funding Number: PA 10 032 Agency: National Institutes of Health Category: Education Health Funding Amount: $200,000 |
| Transdisciplinary Research in Energetics and Cancer (U54) Apply for RFA CA 10 006 Funding Number: RFA CA 10 006 Agency: National Institutes of Health Category: Education Health Funding Amount: Case Dependent |
| Prioritizing Molecular Targets for Cancer Prevention with Nutritional Combinations (R01) Apply for PA 10 035 Funding Number: PA 10 035 Agency: National Institutes of Health Category: Education Health Funding Amount: Case Dependent |
| Dissemination and Implementation Research in Health (R01) Apply for PAR 10 038 Funding Number: PAR 10 038 Agency: National Institutes of Health Category: Education Health Funding Amount: Case Dependent |
| Dissemination and Implementation Research in Health (R21) Apply for PAR 10 040 Funding Number: PAR 10 040 Agency: National Institutes of Health Category: Education Health Funding Amount: $200,000 |
| Dissemination and Implementation Research in Health (R03) Apply for PAR 10 039 Funding Number: PAR 10 039 Agency: National Institutes of Health Category: Education Health Funding Amount: $50,000 |
| Critical Illness and Injury in Aging (R03) Apply for PA 10 043 Funding Number: PA 10 043 Agency: National Institutes of Health Category: Education Health Funding Amount: Case Dependent |
| Critical Illness and Injury in Aging (R01) Apply for PA 10 042 Funding Number: PA 10 042 Agency: National Institutes of Health Category: Education Health Funding Amount: Case Dependent |
| Critical Illness and Injury in Aging (R21) Apply for PA 10 044 Funding Number: PA 10 044 Agency: National Institutes of Health Category: Education Health Funding Amount: $200,000 |
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| Coordination Center for Transdisciplinary Research in Energetics and Cancer (Limited Competition U01) Apply for RFA CA 10 501 Funding Number: RFA CA 10 501 Agency: National Institutes of Health Category: Education Health Funding Amount: Case Dependent |
| Support Opportunity for Addiction Research (SOAR) for New Investigators (R03) Apply for RFA DA 10 015 Funding Number: RFA DA 10 015 Agency: National Institutes of Health Category: Education Health Funding Amount: Case Dependent |
| Development of Multifunctional Drug and Gene Delivery Systems (R01) Apply for PAR 10 048 Funding Number: PAR 10 048 Agency: National Institutes of Health Category: Education Health Funding Amount: Case Dependent |
| Cognitive Remediation Approaches to Improve Drug Abuse Treatment Outcomes (R01) Apply for RFA DA 10 006 Funding Number: RFA DA 10 006 Agency: National Institutes of Health Category: Education Health Funding Amount: Case Dependent |
| Cognitive Remediation Approaches to Improve Drug Abuse Treatment Outcomes (R21) Apply for RFA DA 10 007 Funding Number: RFA DA 10 007 Agency: National Institutes of Health Category: Education Health Funding Amount: $200,000 |
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