June 2024
Volume 65, Issue 7
Open Access
ARVO Annual Meeting Abstract  |   June 2024
Machine Learning-driven Peptide Engineering for Sustained Ocular Drug Delivery
Author Affiliations & Notes
  • Laura Ensign
    Johns Hopkins University, Baltimore, Maryland, United States
  • Footnotes
    Commercial Relationships   Laura Ensign None
  • Footnotes
    Support  NIH grant R01EY026578, R01EY031041
Investigative Ophthalmology & Visual Science June 2024, Vol.65, 5595. doi:
  • Views
  • Share
  • Tools
    • Alerts
      ×
      This feature is available to authenticated users only.
      Sign In or Create an Account ×
    • Get Citation

      Laura Ensign; Machine Learning-driven Peptide Engineering for Sustained Ocular Drug Delivery. Invest. Ophthalmol. Vis. Sci. 2024;65(7):5595.

      Download citation file:


      © ARVO (1962-2015); The Authors (2016-present)

      ×
  • Supplements
Abstract

Presentation Description : We describe engineering of multifunctional peptides that efficiently enter cells and bind to melanin to act as a sustained-release depot in the eye. When the lead multifunctional peptide (HR97) was conjugated to brimonidine and injected in rabbits, intraocular pressure reduction was observed for up to 18 days. Further, the cumulative intraocular pressure lowering effect increased ~17-fold compared to free brimonidine injection. When HR97 was conjugated to sunitinib, effective protection of retinal ganglion cells was observed in a rat optic nerve crush model for up to 2 weeks after the last dose. Further, daily topical dosing for 7 days in rabbits led to effective drug concentrations in the retina. Engineered multifunctional peptide-drug conjugates have the potential to provide sustained therapeutic delivery in the eye to improve treatment efficacy and patient quality of life.

This abstract was presented at the 2024 ARVO Annual Meeting, held in Seattle, WA, May 5-9, 2024.

×
×

This PDF is available to Subscribers Only

Sign in or purchase a subscription to access this content. ×

You must be signed into an individual account to use this feature.

×