Release of Ciprofloxacin and Moxifloxacin From Daily Disposable Contact Lenses From an In Vitro Eye Model
Bibliographic record
Abstract
PURPOSE: To analyze the release of two fluoroquinolones, ciprofloxacin and moxifloxacin, from conventional hydrogel (CH) and silicone hydrogel (SH) daily disposable contact lenses (CLs), comparing release from a fixed-volume vial and a novel in vitro eye model. METHODS: Four CH CLs (nelfilcon A, omafilcon A, etafilcon A, ocufilcon B) and three SH CLs (somofilcon A, narafilcon A, delefilcon A) were used. The lenses were incubated in drug solutions for 24 hours. After the incubation period, the lenses were placed in two release conditions: (1) a vial containing 4.8 mL PBS for 24 hours and (2) an in vitro eye model with a flow rate at 4.8 mL over 24 hours. RESULTS: Release in the vial for both drugs was rapid, reaching a plateau between 15 minutes and 2 hours for all lenses. In contrast, under physiological flow conditions, a constant and slow release was observed over 24 hours. The amounts of ciprofloxacin released from the lenses ranged between 49.6 ± 0.7 and 62.8 ± 0.3 μg per lens in the vial, and between 35.0 ± 7.0 and 109.0 ± 5.0 μg per lens in the eye model. Moxifloxacin release ranged from 24.0 ± 4.0 to 226.0 ± 2.0 μg per lens for the vial, and between 13.0 ± 2.0 and 151.0 ± 10.0 μg per lens in the eye model. In both systems and for both drugs, HEMA-based CLs released more drugs than other materials. CONCLUSIONS: The parameters of the release system, in particular the volume and flow rate, have a significant influence on measured release profiles. Under physiological flow, release profiles are significantly slower and constant when compared with release in a vial.
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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) | 0.001 | 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 | 0.000 |
| 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".