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The Award database is continually updated throughout the year. As a result, data for FY21 is not expected to be complete until September, 2022.

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. Oxygen Production and Delivery on Demand

    SBC: Global Research and Development Inc.            Topic: DHA17B005

    This proposal is in response to the Defense Health Agency 2017 Phase I SBIR topic 17B-005.The approach is the use of a membrane oxygen pump using newly developed nano-thickness membranes with all the layers less than 1 micron total.Nanometer thickness membranes enable more oxygen output per surface area at temperatures of 300-600 C than current state-of-the -art 600-800 C membranes that are 50-300 ...

    STTR Phase I 2018 Department of DefenseDefense Health Agency
  2. Probabilistic Pharmacokinetic Models for Diagnosis, Prognosis, and Personalized Treatment

    SBC: BARRON ASSOCIATES, INC.            Topic: DHA17B003

    Clinicians have recognized that the nature of diseases can be highly individual resulting in different patterns of onset and progression. In turn, the response of an individual to drugs is also unique and governed by a variety of factors. Pharmacokinetic models represent the movement of a drug through the body, and personalized pharmacokinetic models aim to capture the unique responses of specific ...

    STTR Phase I 2018 Department of DefenseDefense Health Agency
  3. 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 Agency
  4. INSPIRE- In-Mask Sensors for Physiological Investigation of Respiratory Exhalation

    SBC: MAKEL ENGINEERING, INC.            Topic: DHP16C002

    Makel Engineering, Inc. and Sandia National Laboratories propose to demonstrate an advanced multi-modal sensor system for in-situ analysis of exhaled volatile organic compounds (VOCs) for pilots, divers and field patients. The In-Mask Sensors for Physiological Investigation of Respiratory Exhalation – INSPIRE combines a micro-gas chromatograph (?GC) and miniature ion mobility spectrometer (IMS) ...

    STTR Phase II 2018 Department of DefenseDefense Health Agency
  5. Functionalized, Therapeutic-Loaded Liposomes for the Acute Treatment of TBI

    SBC: Luna Innovations Incorporated            Topic: DHA18A001

    Traumatic brain injury is a common problem in both the military and civilian communities, but current treatment protocols are focused on managing symptoms and fail to prevent significant long-term repercussions. In the proposed program, Luna will demonstrate the feasibility of a liposome-based therapeutic delivery system capable of delivering hydrophilic and hydrophobic therapeutics to the traumat ...

    STTR Phase I 2018 Department of DefenseDefense Health Agency
  6. Principled Design of an Augmented Reality Trainer for Medics

    SBC: Unveil LLC            Topic: DHP17A003

    Augmented reality (AR) offers the ability to enhance existing combat medic training by including perceptual cues and adaptive training elements to traditional simulation-based training using manikins. Unveil has developed a training system called the Macrocognitive AR Trainer (MART). MART is designed to foster the development of macrocognitive skills (e.g., sensemaking, assessment skills, mental m ...

    STTR Phase II 2018 Department of DefenseDefense Health Agency
  7. Medical Device to Assess the Viability of Tissue Prior to Skin Grafting

    SBC: Spectral Md, Inc.            Topic: DHP17A006

    The primary objective of this Phase II proposal is to construct and validate the portable SpectralMD DeepView imaging technology designed previously in Phase I. This device allows surgeons to quickly and objectively assess tissue viability in burn surgery prior to skin grafting. DeepView uses machine learning and multispectral imaging to generate quantitative prognostic images with easily interpre ...

    STTR Phase II 2018 Department of DefenseDefense Health Agency
  8. Dynamic virtual moulage based on thin film adhesive displays

    SBC: ARCHIE MD INC.            Topic: DHA17A002

    Providing Army combat medics with meaningful experience in treatment of battlefield injuries is a particular challenge. Moulage has the potential to assist in acquiring what could otherwise be very hard-to-come-by preparatory experience for distressing real-life emergencies medics and soldiers may encounter in the field. However, current approaches to moulage are limited in their ability to reflec ...

    STTR Phase II 2018 Department of DefenseDefense Health Agency
  9. Non-invasive Telemetric Assessment of Gut Microbiota Activity in Situ

    SBC: NANOHMICS INC            Topic: DHP17A004

    Different regions of the human GI tract exhibit different chemical environments and different digestion metabolites. As a result, these regions support different microorganisms, with gradients in metabolic products along the length of the GI tract. Single-point measurements of microbiome metabolites (e.g. in feces) are insufficient to provide detailed information of physiological status because th ...

    STTR Phase II 2018 Department of DefenseDefense Health Agency
  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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