Opportunity Information: Apply for PA 10 026
Apply for PA 10 026
- 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 (R21)" and is now available to receive applicants.
- Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 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.)
- Each selected applicant is eligible to receive up to $200,000.00 in funding.
- Eligible applicants include: County governments Nonprofits that do not have a 501(c)(3) status with the IRS, other than institutions of higher education Native American tribal organizations (other than Federally recognized tribal governments) Public and State controlled institutions of higher education Independent school districts Small businesses Others (see text field entitled Additional Information on Eligibility for clarification) Private institutions of higher education Native American tribal governments (Federally recognized) State governments For profit organizations other than small businesses Nonprofits having a 501(c)(3) status with the IRS, other than institutions of higher education City or township governments 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) funding opportunity PA-10-026, titled "Development, Application, and Evaluation of Prediction Models for Cancer Risk and Prognosis (R21)," supports early-stage, exploratory research projects that strengthen how cancer risk and prognosis are predicted. The overall aim is to improve existing prediction models or build new ones by using data that already exist, then validating those models and testing whether they are genuinely useful in research and real clinical settings. The announcement is aimed at teams that can bridge disciplines such as clinical medicine, epidemiology, genetics, statistics, and translational research, with an emphasis on cancer control and prevention as well as clinically relevant prognostic prediction.
A central focus of the FOA is helping investigators tackle two recurring problems that limit prediction modeling in cancer. The first is the practical and scientific challenge of integrating many different kinds of information into a single modeling framework. The FOA explicitly points to combining diverse data types such as clinical and demographic factors, pathology, environmental and epidemiologic exposures, outcomes data, and genetic information, often coming from different databases, repositories, or data warehouses. The second major challenge is rigorous validation, meaning the model should be tested beyond the original development dataset. The FOA stresses validation across multiple separate populations and encourages applicants to quantify real-world performance using measures like sensitivity, specificity, and positive and negative predictive values, rather than relying only on internal fit or a single cohort.
The work encouraged under this opportunity includes developing new risk models (for predicting who might develop cancer) and prognostic models (for predicting outcomes among people who already have cancer), refining existing models with better data integration or methodology, and evaluating how well these tools perform when they are applied in practice. The intended end users include not only researchers, but also clinicians and, in some cases, the general public, reflecting the broader goal of making prediction tools more accurate, interpretable, and actionable in decision-making.
At the same time, the FOA draws a clear boundary around what it will not support. Applications centered on discovering or characterizing prognostic or diagnostic biomarkers or markers, by themselves, are considered out of scope. In other words, the emphasis is on prediction modeling (development, validation, and utility evaluation), not on marker discovery as the primary scientific objective.
This announcement uses the NIH Exploratory/Developmental Research Grant Award (R21) mechanism, which is typically designed for innovative, higher-risk, early-stage projects that can generate proof-of-concept results or key preliminary evidence. The FOA runs in parallel with a companion announcement of the same scientific scope that uses the R01 mechanism (PA-10-025), which is generally more suited to larger, more mature projects. For PA-10-026, the listed award ceiling is $200,000, cost sharing is not required, and awards depend on the availability of funds and the number and quality of applications received.
Eligibility is broad and includes a wide range of organization types: state and local governments (including county and city/township entities), federally recognized tribal governments and other tribal organizations, public and private institutions of higher education, nonprofits (both 501(c)(3) and certain non-501(c)(3) entities), independent school districts, special district governments, small businesses, and other for-profit organizations. The eligibility language also indicates additional eligible applicants may include certain federal agencies, U.S. territories or possessions, and non-U.S. (foreign) organizations, as specified in the full announcement.
Key administrative details in the source record include that the opportunity was posted and created on November 16, 2009, and it originally closed on January 7, 2013 (with the same current closing date listed), with an archive date of February 7, 2013. The listing is associated with CFDA number 93.399 (Cancer Control) and is issued by the National Institutes of Health, with NCI as the lead institute and involvement from NCI divisions focused on both population sciences/cancer control (DCCPS) and treatment/diagnosis (DCTD). For full text and official guidance, the announcement points to the NIH Grants Guide page at http://grants.nih.gov/grants/guide/pa-files/PA-10-026.html.
Frequently Asked Questions (FAQs)
What is PA-10-026?
PA-10-026 is a National Cancer Institute (NCI) funding opportunity announcement titled "Development, Application, and Evaluation of Prediction Models for Cancer Risk and Prognosis (R21)." It supports early-stage, exploratory projects focused on improving how cancer risk and cancer prognosis are predicted.
What is the main purpose of this funding opportunity?
The purpose is to strengthen cancer risk and prognostic prediction by improving existing prediction models or developing new ones using already-existing data, then validating those models beyond the original development dataset and evaluating whether they are useful in research and real clinical settings.
What types of prediction models does the FOA support?
The FOA supports:
- Cancer risk models that predict who might develop cancer.
- Cancer prognostic models that predict outcomes among people who already have cancer.
- Projects that refine or improve existing models through better data integration or improved methodology.
- Projects that evaluate real-world performance and utility of prediction tools when applied in practice.
What research stage and grant mechanism does PA-10-026 use?
This FOA uses the NIH Exploratory/Developmental Research Grant Award (R21) mechanism, which is intended for innovative, higher-risk, early-stage research that can produce proof-of-concept findings or key preliminary evidence.
How does this R21 opportunity relate to the companion R01 announcement?
PA-10-026 runs in parallel with a companion announcement with the same scientific scope that uses the R01 mechanism: PA-10-025. The R01 mechanism is generally aimed at larger and more mature projects compared with R21.
What scientific and practical challenges does the FOA highlight?
The FOA highlights two recurring challenges in cancer prediction modeling:
- Integrating diverse data types into a single modeling framework (for example, combining clinical, demographic, pathology, environmental, epidemiologic, outcomes, and genetic information that may come from different databases or repositories).
- Rigorous validation beyond the development dataset, including validation across multiple separate populations and reporting real-world performance metrics.
What types of data does NCI expect projects to integrate for modeling?
The FOA explicitly mentions integrating diverse information such as clinical and demographic factors, pathology data, environmental and epidemiologic exposures, outcomes data, and genetic information. These inputs may come from different databases, repositories, or data warehouses.
What does the FOA mean by "rigorous validation" of prediction models?
Rigorously validating a model means testing it beyond the original dataset used to develop it. The FOA emphasizes validation across multiple separate populations and encourages reporting performance using measures like sensitivity, specificity, and positive and negative predictive values rather than relying only on internal model fit or results from a single cohort.
What outcomes or performance measures are encouraged?
The FOA encourages applicants to quantify real-world predictive performance using measures such as sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).
Who are the intended end users of the prediction tools supported by this FOA?
The intended end users include researchers, clinicians, and in some cases the general public. The overall intent is to make prediction tools more accurate, interpretable, and actionable for decision-making in research and clinical contexts.
Is this opportunity focused on cancer control and prevention, clinical prognosis, or both?
Both. The FOA emphasizes cancer control and prevention as well as clinically relevant prognostic prediction.
What kinds of projects are out of scope for PA-10-026?
Applications focused primarily on discovering or characterizing prognostic or diagnostic biomarkers or markers by themselves are considered out of scope. The FOA is centered on prediction modeling (development, validation, and utility evaluation) rather than marker discovery as the primary objective.
What is the award ceiling for PA-10-026?
The listed award ceiling is $200,000.
Is cost sharing required?
No. Cost sharing is not required.
Are awards guaranteed if an application is submitted?
No. Awards depend on the availability of funds and the number and quality of applications received.
Who is eligible to apply?
Eligibility is broad and includes many organization types, including:
- State and local governments (including county and city/township entities)
- Federally recognized tribal governments and other tribal organizations
- Public and private institutions of higher education
- Nonprofits (501(c)(3) and certain non-501(c)(3) entities)
- Independent school districts
- Special district governments
- Small businesses
- Other for-profit organizations
The eligibility language also indicates that certain federal agencies, U.S. territories or possessions, and non-U.S. (foreign) organizations may be eligible as specified in the full announcement.
Which agency and institute are sponsoring this opportunity?
This opportunity is issued by the National Institutes of Health (NIH), with the National Cancer Institute (NCI) as the lead institute. The listing references involvement from NCI divisions focused on population sciences/cancer control (DCCPS) and treatment/diagnosis (DCTD).
What is the CFDA number associated with this opportunity?
The listing is associated with CFDA number 93.399 (Cancer Control).
When was this opportunity posted, and what are the key dates shown?
In the provided record, the opportunity was posted and created on November 16, 2009. It originally closed on January 7, 2013 (with the same current closing date listed) and shows an archive date of February 7, 2013.
Where can applicants find the official full text and guidance?
The FOA directs readers to the NIH Grants Guide page for the full announcement: http://grants.nih.gov/grants/guide/pa-files/PA-10-026.html
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| 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 |
| Academic Career Award (Parent K07) Apply for PA 10 058 Funding Number: PA 10 058 Agency: National Institutes of Health Category: Education Health Funding Amount: Case Dependent |
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