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Developmental Research in Cancer Prognosis and Prediction (R33)

Sector: Education • Location: United States of America

Source: Grants.gov

Project
Archived

Purpose. This Funding Opportunity Announcement (FOA), issued by the National Cancer Institute (NCI), National Institutes of Health (NIH), encourages research applications from institutions and organizations to evaluate the utility and pilot the application of new strategies for determining prognosis or predicting response to therapy for cancer. The purpose of this FOA is to develop biomarkers from

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The project “Developmental Research in Cancer Prognosis and Prediction (R33)” is an infrastructure initiative in the Education sector, located in United States of America. Taiyo aggregates data on it from Grants.gov.

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Description

Description

Purpose. This Funding Opportunity Announcement (FOA), issued by the National Cancer Institute (NCI), National Institutes of Health (NIH), encourages research applications from institutions and organizations to evaluate the utility and pilot the application of new strategies for determining prognosis or predicting response to therapy for cancer. The purpose of this FOA is to develop biomarkers from initial correlative observations into assays or test systems suitable for use in clinical trials or other types of confirmatory clinical research studies. This program will provide tools whose purpose is to improve clinical decision-making in the care of cancer patients. Mechanism of Support. This FOA will use the NIH Exploratory/Developmental Phase II Research Grant (R33) mechanism and runs in parallel with a FOA of identical scientific scope, PA-09-158, that encourages applications under the Exploratory/Developmental (R21) grant mechanism. Funds Available and Anticipated Number of Awards. Because the nature and scope of the proposed research will vary from application to application, it is anticipated that the size and duration of each award will also vary. The total amount awarded and the number of awards will depend upon the mechanism, numbers, quality, duration, and costs of the applications received.

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Source reliability

High

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100%

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