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Award Data
The Award database is continually updated throughout the year. As a result, data for FY22 is not expected to be complete until September, 2023.
Download all SBIR.gov award data either with award abstracts (290MB)
or without award abstracts (65MB).
A data dictionary and additional information is located on the Data Resource Page. Files are refreshed monthly.
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Detecting Substandard, Nonconforming, Improperly Processed and Counterfeit Materiel
SBC: VIBRANT CORPORATION Topic: DLA15C001Vibrant Corporation and Sandia National Laboratories (SNL) propose to apply Process Compensated Resonance Testing (PCRT) to the DLA's need for an NDI method to detect counterfeit, nonconforming and improperly processed materiel. PCRT collects and analyzes the resonance frequencies of a component to detect structural defects, characterize material, analyze population variation, monitor manufacturin ...
STTR Phase I 2016 Department of DefenseDefense Logistics Agency -
Marburg Virus Prophylactic Medical Countermeasure
SBC: Flow Pharma, Inc. Topic: CBD18A002Through this STTR contract, we propose to evaluate the efficacy of our vaccine, FlowVax Marburg, in nonhuman primates (NHPs). This will be achieved through four Tasks. In Task 1, we will manufacture the vaccine in a quantity sufficient for the animal studies. In Task 2, we will perform MHC genotyping on a representative population of NHPs and, based on results, select a set of MHC-matched NHPs for ...
STTR Phase II 2020 Department of DefenseOffice for Chemical and Biological Defense -
Marburg Virus Prophylactic Medical Countermeasure
SBC: MAPP BIOPHARMACEUTICAL, INC. Topic: CBD18A002There are currently no vaccines or therapeutics available for Marburg Virus Disease (MVD). Given the specter of weaponization and the terrible morbidity and high mortality rate of MVD, this represents a critical threat to the operational readiness of the Warfighter. While traditional vaccines have contributed greatly to public health, they have some limitations especially in the context of operati ...
STTR Phase II 2020 Department of DefenseOffice for Chemical and Biological Defense -
Bounding generalization risk for Deep Neural Networks
SBC: Euler Scientific Topic: NGA20A001Deep Neural Networks have become ubiquitous in the modern analysis of voluminous datasets with geometric symmetries. In the field of Particle Physics, experiments such as DUNE require the detection of particle signatures interacting within the detector, with analyses of over a billion 3D event images per channel each year; with typical setups containing over 150,000 different channels. In an ...
STTR Phase I 2020 Department of DefenseNational Geospatial-Intelligence Agency