Eyenuk’s AI Eye Screening System For Diabetic Retinopathy Demonstrates Exceptional Performance In A Prospective, Multi-Center, Pivotal Clinical Trial

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    Investigators Report the EyeArt System Achieved 95.5% Sensitivity,
    86.5% Specificity and 97% Imageability, while Meeting All Primary
    Endpoints with p

    LOS ANGELES–(BUSINESS WIRE)–Eyenuk,
    Inc.
    , a global artificial intelligence (AI) medical technology and
    services company and the leader in real-world applications for AI Eye
    Screening™, announced today results from its landmark prospective,
    multi-center, pivotal clinical trial to validate the EyeArt®
    AI Eye Screening System
    for autonomous detection of diabetic
    retinopathy (DR), a blinding disease estimated to affect 191 million
    people globally by the year 20301. The results were presented
    at the ARVO
    Imaging in the Eye Conference
    by Jennifer Lim, MD, Marion H. Schenk
    Esq. Chair and Professor of Ophthalmology and Director of Retina Service
    at the University of Illinois at Chicago.

    The EyeArt AI Eye Screening System makes in-clinic, real-time DR
    screening possible for any physician, enabling quick and accurate
    identification of patients with referable DR during diabetic patient’s
    regular physician visit. Once the patient’s fundus images have been
    captured and submitted to the EyeArt System, the DR screening results
    are available to view and export to a PDF report in less than 60
    seconds. The EyeArt system can free eye care specialists to focus on
    sight-saving treatment rather than screening for DR.

    Key aspects of this prospective, multi-center, pivotal clinical trial (NCT03112005)
    include:

    • 942 subjects enrolled at 15 centers that included primary care,
      endocrinology, ophthalmology, and retina specialty clinics.
    • EyeArt AI system’s assessment of 2-field undilated images was compared
      to comprehensive clinical reference standard comprising adjudicated
      grading of 4 wide-field dilated stereo images on the ETDRS severity
      scale2. The grading was performed by the Wisconsin Fundus
      Photograph Reading Center.
    • Multiple fundus camera models were included and evaluated with the
      EyeArt AI eye screening system.
    • Board-certified ophthalmologists (in a subset of sites) independently
      performed dilated ophthalmoscopy, the most-prevalent method for DR
      screening today.

    Study results show that all pre-determined primary endpoints were met
    with pdetails
    here):

            Sensitivity

    [95% Confidence Bounds]

          Specificity

    [95% Confidence Bounds]

          Imageability

    [95% Confidence Bounds]

       
    EyeArt system

    with no dilation

          95.5%

    [92.4% – 98.5%]

          86.0%

    [83.7% – 88.4%]

          87.5%

    [85.4% – 89.7%]

    EyeArt system

    with dilation-if-ungradable

          95.5%

    [92.6% – 98.4%]

          86.5%

    [84.3% – 88.7%]

          97.4%

    [96.4% – 98.5%]

                     

    “This study is significant as it shows this AI system is quite accurate
    in determining the presence of referable diabetic retinopathy by a very
    rigorous method which compared the AI results to that of photos read by
    expert graders of diabetic retinopathy,” said Dr. Jennifer Lim, an
    Investigator in the EyeArt pivotal trial. “In this prospective
    multi-center study, we showed feasibility and applicability of this
    system for screening for referable diabetic retinopathy. This holds
    great promise in accomplishing screening of the millions of diabetic
    patients for referable diabetic retinopathy in order to identify those
    at risk of visual loss and refer them for prompt treatment by
    ophthalmologists!” Dr. Lim continued, “The high sensitivity and
    specificity achieved by the EyeArt system shows that it can enable
    point-of-care DR screening and that it is a safe way to identify
    patients with DR who require ophthalmology referrals.”

    “Completion of this EyeArt prospective pivotal trial is an exciting step
    for Eyenuk, and this study once again validates the EyeArt System’s
    exceptional diagnostic sensitivity and specificity without needing
    dilation,” said Kaushal Solanki, PhD, Founder and CEO of Eyenuk. “Today
    I am proud to say that artificial intelligence is living up to its
    promise and can deliver substantial and meaningful impact to patients’
    lives globally. Regular and quality eye screening can soon be accessible
    and affordable to hundreds of millions of people living with diabetes,
    leading to vision preservation for many of them.”

    Eyenuk will showcase its EyeArt AI Eye Screening System at Booth #1637
    in the ARVO Exhibition Hall at the Vancouver Convention Centre.

    About the EyeArt® AI Eye Screening System

    The EyeArt AI Eye Screening System is the most extensively validated AI
    technology for autonomous detection of DR, tested in the real-world on
    more than half million patient visits globally with over two million
    images collected in real-world clinical environments. The EyeArt System
    was developed with funding from the US National Institutes of Health
    (NIH) and is validated by the UK National Health Service (NHS). The
    EyeArt System has CE marking in the EU and a Health Canada license. In
    the US, the EyeArt System is limited by federal law to investigational
    use.

    VIDEO:
    Learn more about the EyeArt AI Eye Screening System for Diabetic
    Retinopathy

    About Diabetic Retinopathy (DR)

    DR is a complication of diabetes caused by damage to the blood vessels
    of the light-sensitive tissue at the back of the eye (retina). It is a
    silently progressing disease that at first may cause no symptoms or only
    mild vision problems. Eventually, it can cause blindness. The condition
    can develop in anyone who has type 1 or type 2 diabetes.3 It
    is estimated that one-third of all patients with diabetes will develop
    DR,4 making it the leading cause of vision loss in
    working-age adults.5

    While DR screening is recommended for all diabetic patients, less than
    half get screened annually1, even in the developed world.
    Since diabetic patients outnumber ophthalmologists by 1,600 to 1 in the
    U.S.,6 there are just not enough eye care specialists to meet
    the DR screening needs of the growing diabetic population. Even for
    those receiving their annual screening, ophthalmology appointment wait
    times for DR screening can be weeks or even months.

    About Eyenuk, Inc.

    Eyenuk, Inc. is a global artificial intelligence (AI) medical technology
    and services company and the leader in real-world AI Eye Screening™ for
    autonomous disease detection and AI Predictive Biomarkers™ for risk
    assessment and disease surveillance. Eyenuk is on a mission to screen
    every eye in the world to ensure timely diagnosis of life- and
    vision-threatening diseases, including diabetic retinopathy, glaucoma,
    age-related macular degeneration, stroke risk, cardiovascular risk and
    Alzheimer’s disease.

    EyeArt is a registered trademark of Eyenuk, Inc.

    http://bit.ly/2vqwHNf

    1 International Diabetes Federation. IDF
    Diabetes atlas
    , Sixth edition
    , Brussels, Belgium. 2015.
    2
    Early Treatment Diabetic Retinopathy Study Research Group Fundus
    photographic risk factors for progression of diabetic retinopathy
    .
    ETDRS report number 12. 1991, Ophthalmology 98(5 Suppl):823–833.
    3
    https://www.mayoclinic.org/diseases-conditions/diabetic-retinopathy/symptoms-causes/syc-20371611
    4
    Yau JW, Rogers SL, Kawasaki R, et al. Global
    prevalence and major risk factors of diabetic retinopathy. Diabetes
    Care
    . 2012;35:556-64. doi: 10.2337/dc11-1909
    5
    Prokofyeva E, Zrenner E. Epidemiology
    of major eye diseases leading to blindness in Europe: a literature review
    Ophthalmic
    Research
    . 2012;47:171-188. doi: 10.1159/000329603
    6
    http://www.icoph.org/ophthalmologists-worldwide.html
    and https://www.cdc.gov/diabetes/pdfs/data/statistics/national-diabetes-statistics-report.pdf

    Contacts

    Media Contact:
    Ida Yenney
    Capwell Communications
    [email protected]
    949-999-3303