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Direct Phase II SBIR Grants to Support Extended Development, Hardening, and Dissemination of Technologies in Biomedical Computing, Informatics, and Big Data Science (R44)

Post Date

June 29th 2015

Application Due Date

April 5th 2017

Funding Opportunity Number

PAR-15-288

CFDA Number(s)

93.113
93.172
93.279
93.350
93.351
93.393
93.394
93.395
93.396
93.399
93.846
93.853
93.855
93.856
93.859
93.866

Funding Instrument Type(s)

Grant

Funding Activity Categories

Education
Environment
Health

Eligibility Categories

Small Businesses

Other Eligible Applicants include the following: 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, may be allowed.

Funding

  • Award Range:

    $None - $None

Grant Description

This funding opportunity announcement (FOA) encourages Small Business Innovation Research (SBIR) grant applications from small business concerns (SBCs) that propose the extended development, maintenance, testing, evaluation, hardening and dissemination of existing biomedical software. This FOA is for applications that have completed the proof of concept Phase I stage-type of research through other (non-SBIR) funding sources. The NIH is interested in promoting a broad base of research and development of a broad base of innovative technologies in biomedical computing, informatics, and Big Data Science that will support rapid progress in areas of scientific opportunity in biomedical research. It is expected that this research and development is conducted in the context of important biomedical and behavioral research problems. As such, applications are intended to develop enabling technologies that could apply to the interests of most NIH Institutes and Centers and range from basic biomedicine to research in all relevant organ systems and diseases. Major themes of research include collaborative environments; data integration; analysis and modeling methodologies; and novel computer science and statistical approaches.New opportunities are also emerging as large and complex data sets are becoming increasingly available to the research community. The proposed work should apply best practices and proven methods for software design, construction, and implementation to extend the applicability of existing technologies in biomedical computing, informatics and big data science to a broader biomedical research community.

Contact Information


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