In vitro tear replenishment system: assessing drug delivery from contact lens biomaterials through corneal epithelial monolayer and multilayer under replenishment conditions
Bibliographic record
Abstract
There is a need to develop improved in vitro ocular models for biocompatibility and drug delivery studies to assess the potential of in vivo performance of contact lenses. By using an in vitro corneal epithelial cell model combined with a tear replenishment method, this study aimed to investigate the delivery of the glaucoma drug latanoprost from contact lenses and compare the dynamic release results to no-replenishment (immersion) conditions. Corneal epithelial cells were grown as a monolayer or multilayer on curved cellulose cell culture inserts. Three contact lens materials (balafilcon A; senofilcon A; etafilcon A), soaked for 24 h in latanoprost, were placed on the curved cornea models (CCM) and drug concentration was determined on the basal (diffusion/transport) and apical (supernatant) sides after 1, 4, 8 and 12 h. The in vitro tear replenishment was achieved via intermittent flow of a tear solution over the CCM at a rate of 1 mL/hour. A zero-order kinetic was observed for basal drug concentration over the 12 h period. Similar basal and apical drug concentrations were observed with monolayer and multilayer CCM, except for the etafilcon A material. The apical release of latanoprost was significantly lower under replenishment compared to no-replenishment conditions. These results demonstrate the role that a dynamic release model will have in predicting the amount of drug that can be released from a contact lens into the tear film and the critical role of a cell monolayer in in vitro drug delivery studies.
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How this classification was reachedexpand
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 | 0.001 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".