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Academic-Industrial Partnerships for Translation of in vivo Imaging Systems for Cancer Investigations

 

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Monday, October 05, 2015
 

Summary:

This Funding Opportunity Announcement (FOA) encourages applications from research partnerships formed by academic and industrial investigators to accelerate the translation of either preclinical or clinical in vivo imaging systems and/or methods that are designed to solve a targeted cancer problem. The proposed imaging system/methods may include single or multi-modality in vivo imaging and spectroscopy systems, image-guided and drug delivery systems, image analysis, and related research resources. This FOA may also include, as a secondary goal, support for other laboratory imaging or reference methods as required to validate the performance of the proposed in vivo imaging system and/or methods. Funding may be requested to enhance, adapt, optimize, validate, and otherwise translate the following examples, among others: (a) current commercially supported imaging systems/methods, (b) next-generation imaging systems/methods, (c) quality assurance and quality control methods, (d) validation and correlation studies, (e) quantitative imaging methods, and (f) related research resources.

Because appropriate applications must be translational in scope, this FOA defines innovation as a coherent translational plan to deliver emerging or new capabilities for preclinical or clinical use that are not yet broadly employed in preclinical or clinical settings. The partnerships on each application should establish an inter-disciplinary, multi-institutional research team to work in strategic alliance to implement a coherent strategy to develop and translate their proposed imaging system/methods to solve a targeted cancer problem. This FOA will support clinical trials that emphasize optimization and validation of the performance of imaging systems, including devices, agents and/or methods. This FOA will not support commercial production, or basic research projects that do not emphasize translational development and optimization of the methods for a targeted cancer problem.

For more infromation, please visit:

http://grants.nih.gov/grants/guide/pa-files/PAR-13-169.html

 
 

 

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