Determination of the release of PEG and HPMC from nelfilcon A daily disposable contact lenses using a novel <i>in vitro</i> eye model
Bibliographic record
Abstract
The traditional method to measure release of components from CLs is a vial containing a static volume of PBS (phosphate buffered saline). However, this model does not simulate physiologically relevant tear volume and natural tear flow, air exposure, and mechanical rubbing. These factors can significantly impact release kinetics. We have developed an in vitro eye model (OcuFlow) that simulates these parameters. The aim of the study was to measure the release of PEG (polyethylene glycol), and HPMC (hydroxypropyl methylcellulose) from a daily disposable hydrogel contact lens material (nelfilcon A; Dailies AquaComfort PLUS; DACP;) over 24 hrs using the OcuFlow platform. The elution of PEG and HPMC from DACP lenses was analyzed using LCMS (liquid chromatography mass spectrometry). The release of all wetting agents from the lenses followed a burst release pattern, which occurred within the first 1.5 hrs (P < 0.05). The release of PEG was greater than that of HPMC (P < 0.05). The amount of PEG and HPMC released at any given time was less than 1% of the amount in the blister pack solution. Our results suggest that HPMC and PEG are rapidly released from the CL.
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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 | 0.000 |
| 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 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".