Polymeric Propranolol Nanoparticles for Intraocular Delivery: Formulation, Characterization, and Vitreous Pharmacokinetics
Why this work is in the frame
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Bibliographic record
Abstract
Purpose: Recent studies have reported the promising effect of intravitreal propranolol on retinal neovascularization. However, rapid clearance and short half-life of the drug in the vitreous are the main drawbacks of this therapeutic approach. This study investigates the extension of the residence time of propranolol in the vitreous by polymeric nanoparticles (NPs) with the prospect of improving choroidal neovascularization treatment. Methods: The poly (lactic-co-glycolic) acid (PLGA) NPs were fabricated by a modified double emulsion solvent evaporation method and the obtained NPs were characterized for their size, poly dispersity index (PDI), and surface image. The in vitro release, cell cytotoxicity, and uptake of NPs were also evaluated. To investigate the effect of the vitreous pharmacokinetic drug loaded NPs versus that of the free propranolol, they were intravitreally injected into the rabbits’ eyes and the drug vitreous concentrations in defined intervals were analyzed by high performance liquid chromatography (HPLC). Results: The spherical NPs with about 230 nm size, and almost 10% drug loading were obtained. Based on the 3-(4, 5-Dimethylthiazol-2-Yl)-2, 5-Diphenyltetrazolium Bromide (MTT) outcomes, 30 µg/ml of propranolol was considered as the guide dosage in the intravitreal injection. Confocal microscopy images verified the presence of labeled NPs in the posterior segment after five days of receiving the injection. In vivo assay revealed that the vanishing rate of propranolol in rabbits treated with propranolol NPs was reduced at twice the rate as compared to that of the vanishing rate experienced with only the free drug. Conclusion: PLGA NPs can prolong the existence of propranolol in both vitreous and posterior ocular tissues, and thus, may provide an effective approach in treatment of posterior segment neovascularization.
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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 | 0.000 |
| 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 it