Drug releasing contact lenses and their application to disease presentations
Bibliographic record
Abstract
Eye drops, the most common method for anterior segment treatment, face challenges of inefficiency, with less than 7% instilled drugs typically reaching target tissues of interest. The advent of contact lens drug delivery systems offers a paradigm shift, enhancing drug residence time and bioavailability on the ocular surface. This review focuses on the considerations and challenges in developing contact lenses for drug delivery, particularly for managing four categories of ocular diseases: anterior segment infections, dry eye disease, ocular allergies, and glaucoma. Each disease category requires tailored therapeutic approaches, and the technical intricacies of drug-releasing contact lenses must address concerns related to lens properties, drug release duration, and safety. The aim of this review is to provide insights into the therapeutic needs of ocular diseases and offer a comprehensive overview of the progress made in this innovative approach. The emergence of a commercially available ketotifen fumarate-releasing lens serves as a testament to the feasibility and potential benefits of this innovative approach, paving the way for further refinement and targeted applications in ocular therapeutics.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".