Machine learning to design peptides for eye medicines
Maryland and Johns Hopkins will use a $2.35 million grant to develop machine-learning-designed peptides for longer-lasting eye medicines.
Event / data period: 2026-10-14
Published: · Updated:
Researchers at the University of Maryland and Johns Hopkins plan to use machine learning to design drug-delivery peptides intended to bind ocular melanin, penetrate eye tissue and remain non-toxic. A new $2.35 million National Eye Institute grant supports preclinical laboratory work on longer-lasting eye medicines.
The project builds on a 2023 study in which a 12-amino-acid peptide extended the eye retention of the glaucoma drug brimonidine from eight days to as long as 18 days. The new project has not produced a clinically tested drop or a treatment that replaces injections.
Data
Research announcement
- · Occurred
Machine learning to design peptides for eye medicines
Maryland and Johns Hopkins will use a $2.35 million grant to develop machine-learning-designed peptides for longer-lasting eye medicines.
Methodology
The event date follows the source institution’s announcement. Results are limited to the study or institutional report; prospective applications are not presented as completed products or clinical outcomes.
Updated:
Source-reported indicators
- Announced NEI research grant
- 2.35 million USD
- 2026-10-14 · Observed
Methodology
These are source-announced grants or study indicators; the date is the report day. Grants are not expenditure; classification and chemistry findings retain the reported experiment/model scope.
Updated:
Subjects and places
Subject proposals
- Artificial intelligenceSuggested
- Subject suggested from the title or summary: Machine learningwww.umiacs.umd.edu ↗
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- United States · Place role: Coverage · Place type: Country or area · Location precision: RegionalEvidence
- Explicit preserved editorial country/region; no city or national centroid inferredwww.umiacs.umd.edu ↗