grant

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

Organization IHEALTHSCREEN, INC.Location Richmond Hill, UNITED STATESPosted 1 May 2021Deadline 31 Jul 2027
NIHUS FederalResearch GrantFY2025AAC2AI basedActive Follow-upAffectAge related macular degenerationAge-Related MaculopathyAmericanAnti-VEGFAnti-VEGF Humanized Monoclonal AntibodyAnti-VEGF RhuMAbArylamide Acetylase 2Atrophic AMDAtrophic age-related macular degenerationAttorneysAwardBlindnessCPT CodesCheck-upChronic CareClinicClinicalClinical TrialsCodeCoding SystemColorComputer softwareCounselingCurrent Procedural Terminology CodesDataData SetDeveloped CountriesDiagnosisDoppler OCTDrugsDry AMDDrynessEarly DiagnosisEarly InterventionEarly identificationEarly treatmentEvaluationEyeEye diseasesEyeballFundus photographyGenerationsGoalsGuidelinesHumanImageImplantIncentivesIncidenceIndividualIndustrialized CountriesIndustrialized NationsInjectionsInterventionLaser ElectromagneticLaser RadiationLasersLawyersLeadLegal patentMarketingMedicationMethodsMineralsMoAb VEGFModelingModern ManMonitorMonoclonal Antibody Anti-VEGFN-Acetyltransferase 2NAT-2NAT2NAT2 geneNational Institutes of HealthNon-exudative age-related macular degenerationNonexudative age-related macular degenerationOCT TomographyOphthalmologistOphthalmologyOptical Coherence TomographyOutcome StudyPatentsPatientsPb elementPerformancePharmaceutical PreparationsPhasePreventative strategyPreventionPrevention strategyPreventive strategyPrimary CareProtocolProtocols documentationRecombinant Humanized Anti-VEGF Monoclonal AntibodyRecombinant Humanized Monoclonal Antibody to Vascular Endothelial Growth FactorReportingRetinal DegenerationRetinal DiseasesRetinal DisorderRhuMAb VEGFRiskRisk FactorsRisk ReductionSBIRSalesSightSmall Business Innovation ResearchSmall Business Innovation Research GrantSoftwareSpecificitySupplementationSystemTreatment CostUnited States National Institutes of HealthValidationVisionVisitVisual AcuityVitaminsactive followupage associatedage correlatedage dependentage dependent macular degenerationage induced macular degenerationage linkedage relatedage related macular diseaseage related macular dystrophyage specificartificial intelligence basedbevacizumabcardiovascular riskcardiovascular risk factorcheckupcheckup examinationcommercializationcomputer based predictioncostdegenerative retina diseasesdeveloped countrydeveloped nationdeveloped nationsdiabetes managementdiabetes mellitus managementdiabetic managementdiabetic patientdisease diagnosisdrug/agentdry age-related macular degenerationearly detectionearly therapyeye disordereye fundus photographyfollow upfollow-upfollowed upfollowupfundus cameraheavy metal Pbheavy metal leadimagingimprovedmedical collegemedical schoolsmeetingmeetingsneovascularizationocular diseaseocular disorderophthalmopathyoptical Doppler tomographyoptical coherence Doppler tomographyphase 2 studyphase II studyphotobiomodulationprediction algorithmpredictive modelingpredictive toolspreventpreventingprimary care settingprognosticprogression riskprospectiverecruitreduce riskreduce risksreduce that riskreduce the riskreduce these risksreduces riskreduces the riskreducing riskreducing the riskretina degenerationretina diseaseretina disorderretinal degenerativeretinal degenerative diseasesretinopathyrhuMabVEGFrisk-reducingschool of medicinescreeningscreeningssenile macular diseasesoftware as a medical devicesoftware as a servicesoftware as medical devicesuccessvalidationsvision lossvisual functionvisual loss
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Full Description

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.

Grant Number: 5R44EY031202-05
NIH Institute/Center: NIH

Principal Investigator: Alauddin Bhuiyan

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