Pivotal Trial of an Automated AI-based System for Early Diagnosis and Prediction of Late Age-related Macular Degeneration

NCT ID: NCT07084883

Last Updated: 2025-08-28

Basic Information

• Recruitment Status: RECRUITING
• Total Enrollment: 1076 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2024-08-01
• Study Completion Date: 2027-07-31

Brief Summary

The purpose of this study is to perform a pivotal trial of iPredict, an automated AI-based system for early diagnosis and prediction of late AMD in primary care and ophthalmology settings. Patients will be invited to participate in this study by having non-dilated photos of their eyes taken by an FDA approved fundus camera (DRSPlus from Centervue Inc., CA), at their primary care doctor's office or general ophthalmologist office. The photos will then be transmitted securely and analyzed by computer in the cloud (telemedicine features). Sufficient accuracy of the automatic system has been established compared to the ophthalmologist's diagnosis. In this study, we aim to validate the system against the prospectively taken OCT image and color fundus images.

Detailed Description

The purpose of this study is to perform a pivotal trial of iPredict, an automated AI-based system for early diagnosis and prediction of late AMD in primary care and ophthalmology settings. Patients will be invited to participate in this study by having non-dilated photos of their eyes taken by an FDA approved fundus camera (DRSPlus from Centervue Inc., CA), at their primary care doctor's office or general ophthalmologist office. The photos will then be transmitted securely and analyzed by computer in the cloud (telemedicine features). Sufficient accuracy of the automatic system has been established compared to the ophthalmologist's diagnosis. In this study, we aim to validate the system against the prospectively taken OCT image and color fundus images.

Background AMD affects 15 million Americans, with 200,000 new cases diagnosed each year. At present, there is no treatment for dry AMD. Besides blindness, AMD has other indirect complications such as depression, social dependency, and the risk of fall and injury. The prevalence of this disease is expected to grow substantially as life expectancy continues to increase and record numbers of Baby Boomers enter their senior years. The total direct cost of AMD is $220 billion per year and is expected to increase ~1.5 fold. The Age-Related Eye Disease Study (AREDS) showed that specific vitamin supplementation protocols can reduce the risk of progression from intermediate to late AMD by ~25% which in turn could lower the cost of AMD 17.6% if fully implemented. To accomplish this, it is crucial to perform large scale population screening to identify the individuals with early- or intermediate-stage of AMD and better predict those at risk of developing late AMD, but such a system is currently not available. Although articles have been published on automatic AMD pathology detection, none of these systems are available for screening due to lack of validation and commercial readiness. Considering this urgent need, we aim to develop an automated tool iPredict for early diagnosis and prediction of AMD, and make it widely available in both urban and remote/rural areas and for large- scale screening (through its telemedicine features), and thereby prevent blindness.

Primary and Secondary Study Endpoints The accuracy of the iPredict software developed by iHealthScreen system in early diagnosis of AMD using color retinal photos vs. that of human expert graders for AMD. Also, the prediction of late AMD progression in 1 or two years.

Conditions

Age-related Macular Degeneration (AMD)

Study Design

• Observational Model Type: COHORT
• Study Time Perspective: PROSPECTIVE

Study Groups

One group

One Cohort

No intervention.

Intervention Type: DEVICE

No intervention. Evaluate the automated AMD screening software.

Interventions

No intervention.

No intervention. Evaluate the automated AMD screening software.

Intervention Type: DEVICE

Eligibility Criteria

Inclusion Criteria

• Subjects will be recruited if willing and able to comply with clinic visit and study-related procedures, and provide signed informed consent

Exclusion Criteria

• Already diagnosed with AMD, unable to provide informed consent and currently under treatment of retinal disease.

• Minimum Eligible Age: 50 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

National Institutes of Health (NIH)

NIH

Sponsor Role: collaborator

National Eye Institute (NEI)

NIH

Sponsor Role: collaborator

iHealthScreen Inc

INDUSTRY

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

Alauddin Bhuiyan, PhD

Role: PRINCIPAL_INVESTIGATOR

iHealthScreen Inc

Locations

iHealthScreen Inc.

Richmond Hill, New York, United States

Site Status: RECRUITING

Countries

United States

Central Contacts

Alauddin Bhuiyan

Role: CONTACT

bhuiyan@ihealthscreen.org

718-926-9000

Fariha Nuha, BS (Comp. Biology)

Role: CONTACT

fariha@ihealthscreen.org

718-912-0837

Facility Contacts

Alauddin Bhuiyan

Role: primary

bhuiyan@ihealthscreen.org

718-926-9000

Other Identifiers

R44EY031202

Identifier Type: NIH

Identifier Source: secondary_id

View Link

2024-01-iPredict-AMD

Identifier Type: -

Identifier Source: org_study_id