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The Award database is continually updated throughout the year. As a result, data for FY20 is not expected to be complete until September, 2021.

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.

  1. Handoff Training for Combat Casualty Care (HTC3) Framework

    SBC: PERCEPTRONICS SOLUTIONS, INC.            Topic: DHA17B001

    This proposal is to develop a Handoff Training for Combat Casualty Care (HTC3) Framework.Training is the crux of the handoff problem today. Patient handoffs are a crucial part of casualty care, both in military and civilian environments; and today handoffs are being performed in less than optimal fashion, with ineffective communications accounting for 80% of the handoff errors. Our new HTC3 Framew ...

    STTR Phase I 2018 Department of DefenseDefense Health Program
  2. Marburg Virus Prophylactic Medical Countermeasure

    SBC: MAPP BIOPHARMACEUTICAL, INC.            Topic: CBD18A002

    There are currently no vaccines or therapeutics available for Marburg Virus Disease (MVD). Given the specter of weaponization and the terriblemorbidity and high mortality rate of MVD, this represents a critical threat to the operational readiness of the Warfighter. While traditionalvaccines have proven to be a huge contribution to public health, they do have some limitations especially in the cont ...

    STTR Phase I 2018 Department of DefenseOffice for Chemical and Biological Defense
  3. Combat Casualty Handoff Automated Trainer (CCHAT)

    SBC: SOAR TECHNOLOGY, INC.            Topic: DHA17B001

    Combat casualty handoffs are critical communication moments during which responsibility for the patient and important casualty information is transferred between providers. The nature of these handoffs requires specialized training, for which no standardized framework currently exists. The proposed effort aims to develop a capability, compatible with current DoD systems, that provides caregivers w ...

    STTR Phase I 2018 Department of DefenseDefense Health Program
  4. Novel Circulating RNA-based Markers as Diagnostic Biomarkers of Infectious Diseases

    SBC: 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
  5. CCHAT Handoff Protocol

    SBC: SOAR TECHNOLOGY, INC.            Topic: DHA17B002

    Research has identified that handoffs are particularly important communication processes, during which communication error can lead to patient safety situations. Organizations have created standard practices and training materials to encourage teamwork communication for handoffs, however these do not necessarily capture the needs of military medicine of combat casualty care. Combat casualty handof ...

    STTR Phase I 2018 Department of DefenseDefense Health Program
  6. Griffon Test Suite

    SBC: SOAR TECHNOLOGY, INC.            Topic: DHA17C001

    In this proposal we support the development of a hypoxia test battery by designing and developing a domain general tool suite for processing, synchronizing, and evaluating data from cognitive, behavioral, and physiological measures.The proposed Griffon Tool Suite addresses many of the practical requirements demanded by a flexible test battery. The effort falls into three major thrusts.First, we pr ...

    STTR Phase I 2018 Department of DefenseDefense Health Program
  7. System for Nighttime and Low-Light Face Recognition

    SBC: Polaris Sensor Technologies, Inc.            Topic: SOCOM18A001

    The objective of this proposal is to develop instrumentation and algorithms for acquiring facial features for facial recognition in low- and no-light conditions.We will use cross-spectrum matching by exploiting infrared polarimetric imagery which tends to show features that match more closely visible imagery than conventional infrared.In addition to thermal infrared, we will also test subjects in ...

    STTR Phase I 2018 Department of DefenseSpecial Operations Command
  8. Human Performance Optimization: Ketone Esters for Optimization of Operator Performance in Hypoxia

    SBC: HVMN Inc.            Topic: SOCOM17C001

    In the setting of altitude-induced hypoxia, operator cognitive capacity degrades and can compromise both individual and team performance. This degradation is linked to falling brain energy (ATP) levels and an increased reliance on anaerobic energy production from glucose. Ketone bodies are the evolutionary alternative substrate to glucose for brain metabolic requirements; previous studies have sho ...

    STTR Phase I 2018 Department of DefenseSpecial Operations Command
  9. Marburg Virus Prophylactic Medical Countermeasure

    SBC: Flow Pharma, Inc.            Topic: CBD18A002

    Flow Pharma, Inc. is a biotechnology company in the San Francisco Bay Area developing fully synthetic cytotoxic T lymphocyte (CTL)stimulating peptide vaccines for Marburg virus. The FlowVax vaccine platform allows us to create dry powder formulations of biodegradablemicrospheres and TLR adjuvants incorporating class I and class II T cell epitopes. FlowVax vaccines can be designed for delivery by i ...

    STTR Phase I 2018 Department of DefenseOffice for Chemical and Biological Defense
  10. Hybrid DNN-based Transfer Learning and CNN-based Supervised Learning for Object Recognition in Multi-modal Infrared Imagery

    SBC: TOYON RESEARCH CORPORATION            Topic: 1

    On this effort Toyon Research Corp. and The Pennsylvania State University are developing deep learning-based algorithms for object recognition and new class discovery in look-down infrared (IR) imagery. Our approach involves the development of a hybrid classifier that exploits both transfer learning and semi-supervised paradigms in order to maintain good generalization accuracy, especially when li ...

    STTR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
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