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R44NIH · NATIONAL EYE INSTITUTENIH

A Model for Predicting 2-Year Risk of Incident Late Age-related Macular Degeneration

Bhuiyan, Alauddin (Contact)·IHEALTHSCREEN, INC., NY·2021–2027·ACTIVE
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INSTITUTION

IHEALTHSCREEN, INC., NY

PRINCIPAL INVESTIGATOR

Bhuiyan, Alauddin (Contact)

FUNDING

$698K

YEAR

2021

MOONBASE SCORE

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Abstract

PROJECT SUMMARY Age-related macular degeneration (AMD), in the dry or wet form, is the leading cause of vision loss in developed countries. The Age-Related Eye Disease Study (AREDS) showed that specific vitamin and mineral supplementation reduces the risk of progression from intermediate stages to late AMD and maintains visual acuity in approximately 25% of patients. While treatment of wet AMD with Intraocular injections can be effective in maintaining vision, such treatments are costly and may be associated with significant cardiovascular risks or even progression of dry AMD. Hence, it is critical to identify patients at the earlier stages. With the NIH SBIR Phase II award, iHS has filled this market gap by developing iPredict-AMDTM, an artificial intelligence (AI) based software for screening/early diagnosis and prediction of Late AMD, which needs to be prospectively validated for FDA approval and commercialization. To accomplish this, the prospective clinical trials for iPredict-AMD is required along with other studies such as human factor study and precision study, which will be accomplished through this proposal.

R44NATIONAL EYE INSTITUTESpecial Emphasis Panel[ZRG1-NV-M(12)B]intelligencediagnosisdevelopingidentifyproposalclinicalvisualrelatedtreatmentssignificantsupplementationrequiredprospectivelycommercializationamdtmtreatmentapprovalaccomplishacuity

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