[Federal Register Volume 89, Number 210 (Wednesday, October 30, 2024)]
[Notices]
[Page 86343]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2024-25162]


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DEPARTMENT OF HEALTH AND HUMAN SERVICES

National Institutes of Health


Government Owned Inventions Available for Licensing/
Collaboration: Using Artificial Intelligence To Diagnose Uveitis

AGENCY: National Institutes of Health, HHS.

ACTION: Notice.

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SUMMARY: The National Eye Institute seeks (NEI), an institute of the 
National Institutes of Health (NIH), Department of Health and Human 
Services (HHS), is giving notice of the licensing and collaboration 
opportunity for the inventions listed below, which are owned by an 
agency of the U.S. Government and are available for licensing/
collaboration in the U.S. to achieve expeditious commercialization of 
results of federally-funded research and development.

FOR FURTHER INFORMATION CONTACT: Inquiries related to this licensing/
collaboration opportunity should be directed to: Hiba Alsaffar, Ph.D., 
Technology Transfer Manager, NCI, Technology Transfer Center, Email: 
<a href="/cdn-cgi/l/email-protection#fd95949f9cd39c918e9c9b9b9c8fbd939495d39a928b"><span class="__cf_email__" data-cfemail="9ff7f6fdfeb1fef3ecfef9f9feeddff1f6f7b1f8f0e9">[email protected]</span></a> or Phone: 240-276-7489.

SUPPLEMENTARY INFORMATION: Uveitis is caused by inflammation in the eye 
that can cause pain and reduce vision. The rate of uveitis in the 
United States is 1 in every 200 people with eye-related irritation. 
Permanent symptoms such as vision loss can occur if untreated. 
Therefore, early detection is crucial. In certain uveitis cases, 
fluorescein angiography (FA) is essential for the diagnosis and 
management due to its ability to display retinal vascular leakage 
(RVL). Although proven to be critical in diagnosing and assessing 
severity, FA is invasive and side effects have been reported. 
Additionally, the procedure is time-consuming and imposes economic 
burdens to patients, physicians and payors. Scientists at the NEI have 
developed a deep learning tool to non-invasively detect RVL using 
ultrawide-field color fundus photos. This algorithm identifies fundus 
images with and without RVL with high accuracy (79%) and sensitivity 
(85%). Compared to the current gold standard of assessing RVL 
(clinician interpretation), this deep learning tool provides an 
improved method of detecting RVL for patients with uveitis.
    This Notice is in accordance with 35 U.S.C. 209 and 37 CFR part 
404.
    NIH Reference Number: E-005-2023-0.
    Potential Commercial Applications:
    <bullet> Diagnostic tool to predict uveitis.
    <bullet> Add-on to current color fundus imaging modalities.
    Competitive Advantages:
    <bullet> Greater accuracy and sensitivity versus current gold 
standard to assess RVL (clinician assessment).
    <bullet> Deep learning tool to assess RVL.
    <bullet> Deep learning to assess ultrawide-field color fundus 
images and assess RVL.
    Publication: Young LH, et al. Automated Detection of Vascular 
Leakage in Fluorescein Angiography--A Proof of Concept. (PMID 
35877095).
    Patent Status: US Provisional Application 65/599,446 filed on 
November 15, 2023.
    Development Stage: Prototype.
    Therapeutic Area(s): Eye, Ear, Nose, Throat.

    Dated: October 24, 2024.
Richard U. Rodriguez,
Associate Director, Technology Transfer Center, National Cancer 
Institute.
[FR Doc. 2024-25162 Filed 10-29-24; 8:45 am]
BILLING CODE 4140-01-P


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