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Validation of artificial intelligence (AI) based software as medical device (SaMD) for retinopathy of prematurity (ROP)

Award Information
Agency: Department of Health and Human Services
Branch: National Institutes of Health
Contract: 1R44EY035596-01
Agency Tracking Number: R44EY035596
Amount: $1,907,135.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: NEI
Solicitation Number: PA22-177
Timeline
Solicitation Year: 2022
Award Year: 2023
Award Start Date (Proposal Award Date): 2023-09-30
Award End Date (Contract End Date): 2025-08-31
Small Business Information
1651 VILLAGE PARK LN
Lake Oswego, OR 97034-3774
United States
DUNS: 118570419
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 KARYN JONAS
 (561) 818-2161
 karynjonas@gmail.com
Business Contact
 TONG SUN
Phone: (561) 818-2161
Email: tony@siloamvision.com
Research Institution
N/A
Abstract

The purpose of this application is to perform the necessary clinical studies to seek regulatory approval for an
artificial intelligence (AI) software as medical device (SaMD) for retinopathy of prematurity (ROP) diagnosis.
ROP is a leading cause of childhood blindness worldwide, with approximately 50,000 babies going blind
annually, most of which is preventable with accurate and timely diagnosis. The i-ROP DL algorithm was
developed by the i-ROP research consortium and has been shown to provide expert-level diagnosis of plus
disease, a component of severe ROP, based on images from the Retcam (Natus, Middleton, WI) digital fundus
camera. The output is a vascular severity score (VSS) that corresponds to spectrum of plus disease, as defined
by the International Classification of ROP, and has been endorsed by the Food and Drug Administration (FDA) as
an appropriate output for an ROP SaMD. If incorporated into a clinical workflow, this technology could provide
automated, immediate, expert-level diagnosis of ROP to the bedside, solving one of the key gaps in care that
results in preventable blindness worldwide. The first aim of this project is to update and retrain the i-ROP DL
algorithm to improve speed and repeatability for clinical use, finalize the image quality and pre-processing
pipeline, and integrate it into the iTeleGEN data management system, an ROP telemedicine software platform.
The second aim is to perform the necessary clinical studies for the two proposed indications for use (IFU): The
first IFU will be as an assistive diagnostic study to improve the clinical diagnosis of plus disease with regulatory
approval based on a multi-reader multi-case study with a primary outcome of improved diagnosis of plus disease,
based on a five expert reference standard diagnosis, with the use of the VSS. The second IFU will be for
autonomous ROP screening for more than mild ROP (MTMROP, defined as type 2 or worse according to the
Early Treatment for ROP study definition). The pivotal study will have a primary outcome of 85% sensitivity and
85% specificity for the diagnosis of MTMROP, with a secondary outcome of greater than 95% sensitivity for
detection of treatment-requiring ROP. The third aim of the proposal is to validate the i-ROP DL algorithm on a
digital fundus camera made by Forus Health (Bengaluru, India), a digital eye care company, with ROP camera
distribution in more than 20 countries. If successful, then once FDA approval is obtained on the Retcam it may
be extended through a 510K process to a camera that is more affordable than the Retcam and widely available
in low- and middle-income countries. This work will be done by Siloam Vision, a company started by two of the
inventors of the i-ROP DL algorithm, in conjunction with Oregon Health and Science University. At the end of the
study period, the goal will be to have the necessary data to support FDA approval of the i-ROP DL algorithm for
two IFUs on two digital fundus cameras and being one step closer to bringing this technology to the bedside to
reduce the number of babies going blind from ROP worldwide.

* Information listed above is at the time of submission. *

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