Timolol maleate release from hyaluronic acid-containing model silicone hydrogel contact lens materials
Bibliographic record
Abstract
This study was designed to assess the impact of a releasable wetting agent, such as hyaluronic acid (HA), on the release profile of timolol maleate (TM) from model silicone hydrogel contact lens materials. Polyvinylpyrrolidone (PVP) was used as an alternative wetting agent for comparison. The model lenses consisted of a hydrophilic monomer, either 2-hydroxyethyl methacrylate or N,N-dimethylacrylamide and a hydrophobic silicone monomer of methacryloxypropyltris (trimethylsiloxy) silane. The loading of the wetting and the therapeutic agent occurred during the synthesis of the silicone hydrogels through the method of direct entrapment. The developed materials were characterized by minimal changes in the water uptake, while lower molecular weight of HA improved their surface wettability. The transparency of the examined silicone hydrogels was found to be affected by the miscibility of the wetting agent in the prepolymer mixture as well as the composition of the developed silicone hydrogels. Sustained release of TM from 4 to 14 days was observed, with the drug transport occurring presumably through the hydrophilic domains of the silicone hydrogels. The release profile was strongly dependent on the hydrophilic monomer composition, the distribution of hydrophobic (silane) domains, and the affinity of the therapeutic agent for the silicone hydrogel matrix. Noncovalent entrapment of the wetting agent did not change the in vitro release duration and kinetics of TM, however the drug release profile was found to be controlled by the simultaneous release of TM and HA or PVP. In the case of HA, depending on the HA:drug ratio, the release rate was decreased and controlled by the release of HA, likely due to electrostatic interactions between protonated TM and anionic HA. Overall, partitioning of the drug within the hydrophilic domains of the silicone hydrogels as well as interactions with the wetting agent determined the drug release profile.
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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) | 0.001 | 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".