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The Award database is continually updated throughout the year. As a result, data for FY22 is not expected to be complete until September, 2023.
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Circulating Diagnostic Markers of Infectious DiseaseSBC: PATHOVACS INCORPORATED Topic: CBD18A001
The focus of this STTR phase I component is on proof-of-concept studies demonstrating applicability of technical approaches for identificationof circulatory diagnostic markers for infectious disease. Therefore, the primary objective of this project is to determine feasibility of one suchtechnical approach called Proteomics-based Expression Library Screening (PELS), for identification of pathogen-d ...STTR Phase I 2018 Department of DefenseOffice for Chemical and Biological Defense
Host-Targeted Antiviral Drugs Providing Rapid, Scalable, Stable, Broad-Spectrum MedicalCountermeasure Against Marburg VirusSBC: EVRYS BIO LLC Topic: CBD18A002
In a pandemic or exposure to weaponized Marburg virus the morbidity, mortality and social unrest that will ensue before vaccines orMilitary operating on foreign soil as well as to the population of the US Homeland. Practically all threat agents of biological origin (except forcertain non-proteinaceous toxins, typically produced by marine organisms and fungi) have their structure and vital function ...STTR Phase I 2018 Department of DefenseOffice for Chemical and Biological Defense
Novel Circulating RNA-based Markers as Diagnostic Biomarkers of Infectious DiseasesSBC: CFD RESEARCH CORPORATION Topic: CBD18A001
In resource limited settings, rapid and accurate diagnosis of infections is critical for managing potential exposures to highly virulent pathogens,whether occurring from an act of bioterrorism or a natural event. This is especially important for hard to detect intracellular bacterial andalphavirus infections, that overlap symptomatically and often treated empirically due to a lack of reliable and ...STTR Phase I 2018 Department of DefenseOffice for Chemical and Biological Defense
Algorithms for Look-down Infrared Target ExploitationSBC: Signature Research, Inc. Topic: 1
Signature Research, Inc. (SGR) and Michigan Technological University (MTU) propose a Phase I STTR effort to develop a learning algorithm which exploits the spatio-spectral characteristics inherent within IR imagery and motion imagery.Our archive of modelled and labeled data sets will allow our team to thoroughly capture the variable elements that will drive machine learning performance.The overall ...STTR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency