SBIR/STTR Research Award

Functional phenotyping of leukocyte reprogramming in Type 1 diabetes

Award identifier 157b6a09e082427c33cc563c30283249c69ff4ac7a8df1224f9d188af0af28d1Awarding agency Department of Health and Human Services · National Institutes of Health

Award amount

$547,146

Program and phase

SBIR · Phase I

Award year

2012

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Award details

Awarding agency
Department of Health and Human Services
Branch
National Institutes of Health
Recipient company
CIENCIA INC
Proposal award date
Not reported
Contract end date
Not reported
UEI
Q7TKCXQFD2J1
Solicitation number
DK11-024
Topic code
NIDDK

Research abstract

DESCRIPTION (provided by applicant): Type 1 Diabetes (T1D) affects more than 1 million people in the United States Source ADA http://www.diabetes.org/about-diabetes.jsp and is usually diagnosed in children and can lead to blindness, heart disease and kidney failure. A major focus of intervention for T1D is on the detection and characterization of auto-reactive T cells, which play a central role in the attack on insulin producing islet cells. For medical intervention for T1D to be most effective, the disease should be detected and treated before the onset of symptoms. Current methods to identify the targets of auto-reactive T1D-specific T cells are slow, technically demanding, labor- and reagent-intensive, and consume large numbers of T cells to test limited numbers of targets. Sample size is an extremely important consideration in T1D and is often a limiting factor when testing clinical samples, especially as young children and adolescents are unable to give large samples. The objective of this SBIR application is to develop an automated T cell analysis assay to identify and functionally characterize auto-reactive T1D antigen-specific CD4+ and CD8+ T cells capable of testing hundreds to thousands of targets simultaneously using as little as 2ml of patient sample. The proposed system is based upon integrating patent pending MHC-peptide array technology with an automated flow cell detection and analysis system. The innovative approach to this project will combine a self-contained sample cartridge in which antigen-specific CD4+ and CD8+ auto-reactive T cells bind to high avidity MHC-peptide monomers and are detected via surface plasmon resonance with correlated highly sensitive surface plasmon resonance-enhanced detection of cytokines secreted by identified cellsubpopulations. The goal is to create a T cell analysis system that offers high content screening, multi-parameter characterization capability and incorporates state-of- the-art integrated sample handling for ease-of-use. At present, there are no systems available that offer the breadth of capabilities, the simplicity of use and limited sample size requirements as the proposed T cell analysis system using MHC-peptide arrays in the fight against T1D. PUBLIC HEALTH RELEVANCE: Type 1 Diabetes (T1D) isan autoimmune disease usually diagnosed in children where T cells, part of the body's own immune system, attack pancreas cells that make insulin. Detecting auto-reactive T cells with current methods is impractical, time consuming and requires large patient samples. This application is to develop a high throughput T cell analysis system to detect and characterize auto-reactive T1D T cells using substantially smaller samples. Knowledge gained by the use of this T cell analysis system may lead to the faster discovery of T1D T cell targets, the ability to better monitor T1D therapies in clinical trils and the potential for earlier diagnosis of T1D.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

77 SBIR/STTR records share this UEI (1992–2022). Reported award amounts total $17,671,955. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Health and Human Services, National Aeronautics and Space Administration, Department of Defense, National Science Foundation, Environmental Protection Agency, Department of Energy

Agency intelligence

Department of Health and Human Services

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