Drug releasing contact lenses and their application to disease presentations
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it