SBIR/STTR Research Award

Automated image-based biomarker computation tools for diabetic retinopathy

Award identifier d3dd9c6ee5bb55dae4f5961c26c6a1c69f5c587c234de56523ec1cd42633a79bAwarding agency Department of Health and Human Services · National Institutes of Health

Award amount

$260,857

Program and phase

STTR · 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
EYENUK, INC.
Proposal award date
Not reported
Contract end date
Not reported
UEI
ZCM5S7UD1WT4
Solicitation number
PA11-097
Topic code
NCATS

Research abstract

DESCRIPTION (provided by applicant): In this STTR project, we present EyeMark, a set of tools for automated computation of biomarkers for diabetic retinopathy using retinal image photographs. Specifically, we will develop tools for computation of microaneurysm (MA) appearance and disappearance rates (jointly known as turnover rates) for use as a biomarker in monitoring progression of diabetic retinopathy (DR). The availability of a reliable image-based biomarker will have high positive influence on variousaspects of DR care, including screening, monitoring progression, drug discovery and clinical research. There is ample published evidence that MA turnover rates are a good predictor of likelihood of progression to more severe retinopathy, establishing MA turnover as an excellent biomarker for diabetic retinopathy. Measuring this quantity involves two steps: careful alignment of current and baseline images, and marking of individual MAs. This process is very time consuming and prone to error, if done by entirely by human graders. The primary goal of this project is to overcome the above limitations by automating both the steps involved in MA turnover measurement: accurate image registration, and MA detection. We will develop end-too-end desktop software for automated computation of MA turnover and also provide intuitive visualization tools for clinicians to more effectively monitor diabetic retinopathy progression. PUBLIC HEALTH RELEVANCE: The proposed tool will greatly enhance the clinical care available to diabetic retinopathy patients by providing an automated tool for computation of a biomarker in a non-invasive manner. This will enable identification of patients who are more likely to progress to severe retinopathy, thus helping prevent vision loss in such patients by timely intervention. Early identification is especially important in face of long backlog of diabetic patients waiting for an eye examination, and the fact that 90% of vision loss can be saved by early identification. The availability ofan effective biomarker will also positively influence the drug discovery process by facilitating early and reliable determination of biological efficacy of potential new therapies.

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

13 SBIR/STTR records share this UEI (2012–2020). Reported award amounts total $9,832,543. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Health and Human Services

Agency intelligence

Department of Health and Human Services

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