Rheological Properties, Dissolution Kinetics, and Ocular Pharmacokinetics of Loteprednol Etabonate (Submicron) Ophthalmic Gel 0.38%
Bibliographic record
Abstract
Abstract Purpose: To evaluate rheological properties, in vitro dissolution, and in vivo ocular pharmacokinetics of loteprednol etabonate (LE) (submicron) ophthalmic gel 0.38%. Methods: The viscosity of the LE gel 0.38% formulation was measured with a controlled stress rheometer. Dissolution kinetics were evaluated in a fixed-volume and flow-through assay. Rabbits received a single instillation of LE (submicron) gel 0.38% (both eyes), and concentrations of LE in ocular tissues were determined through 24 h by liquid chromatography with tandem mass spectrometry. Where indicated, comparators included micronized LE gel 0.38%, 0.5% (Lotemax ® gel), and 0.75%. Results: LE (submicron) gel 0.38% exhibited shear-thinning characteristics similar to LE gel 0.5% with nearly identical yield stress. LE (submicron) gel 0.38% released 2.6-fold more LE into the dissolution medium than micronized LE gel 0.5% over 30 s in the fixed-volume dissolution assay, and submicron LE attained higher concentrations of dissolved LE than micronized LE gel 0.38% in the flow-through dissolution assay. In rabbits, the maximal concentration and area-under-the-curve over 24 h for LE in aqueous humor were 2.5- and 1.8-fold higher, respectively, for LE (submicron) gel 0.38% versus micronized LE gel 0.5% (both P < 0.001). Pharmacokinetic parameters were similar for most other tissues. Conclusions: LE (submicron) gel 0.38% demonstrated similar rheological properties to micronized LE gel 0.5% but faster dissolution, thus providing similar or higher LE concentrations in the aqueous humor, cornea, and iris-ciliary body after ocular dosing in rabbits despite a lowered concentration of drug in the formulation.
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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".