Government Owned Inventions Available for Licensing/Collaboration: Using Artificial Intelligence To Diagnose Uveitis, 86343 [2024-25162]
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86343
Federal Register / Vol. 89, No. 210 / Wednesday, October 30, 2024 / Notices
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[FR Doc. 2024–25139 Filed 10–29–24; 8:45 am]
BILLING CODE 4184–34–P
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.
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:
ddrumheller on DSK120RN23PROD with NOTICES1
SUMMARY:
VerDate Sep<11>2014
17:59 Oct 29, 2024
Jkt 265001
hiba.alsaffar@nih.gov 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:
• Diagnostic tool to predict uveitis.
• Add-on to current color fundus
imaging modalities.
Competitive Advantages:
• Greater accuracy and sensitivity
versus current gold standard to assess
RVL (clinician assessment).
• Deep learning tool to assess RVL.
• Deep learning to assess ultrawidefield 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.
PO 00000
Frm 00034
Fmt 4703
Sfmt 4703
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]
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National Institutes of Health
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following meeting.
The meeting will be closed to the
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as amended. The grant applications and
the discussions could disclose
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and personal information concerning
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Time: 10 a.m. to 6 p.m.
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Address: National Institutes of Health,
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Meeting Format: Virtual Meeting.
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Diseases Research; 93.839, Blood Diseases
and Resources Research, National Institutes
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E:\FR\FM\30OCN1.SGM
30OCN1
]]>Agencies
[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]
-----------------------------------------------------------------------
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.
-----------------------------------------------------------------------
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:
[email protected] 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:
Diagnostic tool to predict uveitis.
Add-on to current color fundus imaging modalities.
Competitive Advantages:
Greater accuracy and sensitivity versus current gold
standard to assess RVL (clinician assessment).
Deep learning tool to assess RVL.
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
