Phenylboronic-Acid-Based Polymeric Micelles for Mucoadhesive Anterior Segment Ocular Drug Delivery
Bibliographic record
Abstract
Topical drug delivery to the front of the eye is extremely inefficient due to effective natural protection mechanisms such as precorneal tear turnover and the relative impermeability of the cornea and sclera tissues. This causes low ocular drug bioavailability, requiring large frequent doses that result in high systemic exposure and side effects. Mucoadhesive drug delivery systems have the potential to improve topical drug delivery by increasing pharmaceutical bioavailability on the anterior eye surface. We report the synthesis and characterization of a series of poly(L-lactide)-b-poly(methacrylic acid-co-3-acrylamidophenylboronic acid) block copolymer micelles for use as mucoadhesive drug delivery vehicles. Micelle properties, drug release rates, and mucoadhesion were shown to depend on phenylboronic acid content. The micelles showed low in vitro cytotoxicity against human corneal epithelial cells and undetectable acute in vivo ocular irritation in Sprague-Dawley rats, suggesting good biocompatibility with the corneal surface. The micelles show the potential to significantly improve the bioavailability of topically applied ophthalmic drugs, which could reduce dosage, frequency of administration, and unintentional systemic exposure. This would greatly improve the delivery of the ocular drugs such as the potent immunosuppressive cyclosporine A used in the treatment of severe dry eye disease.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".