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

> **NIH NIH R44** · IHEALTHSCREEN, INC. · 2021 · $45,000

## Abstract

PROJECT SUMMARY
Age-related macular degeneration (AMD), in the dry or wet form, is the leading cause of vision loss in the
developed countries. The Age-Related Eye Disease Study (AREDS) showed that specific antioxidant vitamin
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. Unfortunately, there is no effective, automated screening tool to accomplish this, and the patients
themselves may be asymptomatic. The goal of this SBIR Direct-to-Phase II proposal is to provide such tool.
We have demonstrated the feasibility of AMD screening software ‘iPredictTM’ by successfully identifying 98.1%
of individuals with early or intermediate stage AMD. iPredictTM also successfully predicted which individuals
would develop late AMD within one year with 87.8% accuracy and two years with 88.4% accuracy. iPredictTM
has prototype components for image analysis and machine learning. We also developed a HIPAA compliant
telemedicine platform which will enable iPredictTM to perform large-scale screening from remote and rural
areas. In order to bring the product to market, these components need to be integrated and tested which is the
aim of our proposed Direct-to-Phase II proposal. We aim to develop the finished product which will be ready for
the market. We also aim to evaluate the efficacy of iPredictTM in a clinical setup. The AMD preventative market
is estimated around $5.4 billion in the U.S. alone. iPredictTM will capture the major market share with its best
accuracy and be the first prediction tool for AMD. We aim to commercialize iPredictTM for the screening and
prevention of AMD, saving millions of citizens from blindness and reduced quality of life. With iPredictTM’s
improvements in speed of delivery, cost of care, and ease of access, the product will be a significant addition
to the healthcare system. The iPredictTM’s telemedicine platform will allow large-scale screening from
remote/rural areas, primary care clinics, optometry offices and ophthalmology clinics.

## Key facts

- **NIH application ID:** 10320271
- **Project number:** 3R44EY031202-01A1S1
- **Recipient organization:** IHEALTHSCREEN, INC.
- **Principal Investigator:** Alauddin Bhuiyan
- **Activity code:** R44 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $45,000
- **Award type:** 3
- **Project period:** 2021-05-01 → 2023-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10320271

## Citation

> US National Institutes of Health, RePORTER application 10320271, A Model for Predicting 2-Year Risk of Incident Late Age-related Macular Degeneration (3R44EY031202-01A1S1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10320271. Licensed CC0.

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