OpportunityTitle: Oncology Co-Clinical Imaging Research Resources to Encourage Consensus on Quantitative Imaging Methods and Precision Medicine (U24 - Clinical Trial Optional)
AdditionalInformationOnEligibility: Other Eligible Applicants include the following:  Alaska Native and Native Hawaiian Serving Institutions; Asian American Native American Pacific Islander Serving Institutions (AANAPISISs); Eligible Agencies of the Federal Government; Faith-based or Community-based Organizations; Hispanic-serving Institutions; Historically Black Colleges and Universities (HBCUs); Indian/Native American Tribal Governments (Other than Federally Recognized); Non-domestic (non-U.S.) Entities (Foreign Organizations); Regional Organizations; Tribally Controlled Colleges and Universities (TCCUs) ; U.S. Territory or Possession; Non-domestic (non-U.S.) Entities (Foreign Institutions) are not eligible to apply. Non-domestic (non-U.S.) components of U.S. Organizations are not eligible to apply. Foreign components, as defined in the NIH Grants Policy Statement, are not allowed.
Description: The purpose of this Funding Opportunity Announcement (FOA) is to invite Cooperative Agreement applications to develop research resources that will encourage a consensus on how Quantitative Imaging (QI) methods are optimized to improve the quality of imaging results for co-clinical trials. The scientific goals of this FOA are to: (a) perform the appropriate optimization of the pre-clinical quantitative imaging methods, (b) implement the optimized methods in the co-clinical trial, and finally (c) populate a web-accessible research resource with all the data, methods, workflow documentation, and results collected from the co-clinical investigations. Co-clinical trials are defined in this FOA as investigations in patients and in parallel (or sequentially) in mouse or human-in-mouse models of cancer that mirror the genetics and biology of the patients malignancies or pre-cancerous lesions. The co-clinical trial should include either (a) a therapeutic goal, such as the prediction, staging, and/or measurement of tumor response to therapies, or (b) a screening and early detection or a cancer risk stratification goal for lethal cancer versus non-lethal disease. Applicants are encouraged to organize multi-disciplinary teams with experience in mouse models research, human investigations, imaging platforms, QI methods, decision support software and informatics to populate the research resource.
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GrantorContactText: NIH OER Webmaster&lt;br/&gt;FBOWebmaster@OD.NIH.GOV&lt;br/&gt;