Deferasirox nanosuspension loaded dissolving microneedles for ocular drug delivery
Bibliographic record
Abstract
Deferasirox (DFS) is an oral iron chelator that is employed in retinal ailments as a neuroprotectant against retinal injury and thus has utility in treating disorders such as excitoneurotoxicity and age-related macular degeneration (AMD). However, the conventional oral route of administration can present several disadvantages, e.g., the need for more frequent dosing and the first-pass effect. Microneedles (MNs) are minimally invasive systems that can be employed for intrascleral drug delivery without pain and can advantageously replace intravitreal injections therapy (IVT) as well as conventional oral routes of delivery for DFS. In this study, DFS was formulated into a nanosuspension (NS) through wet media milling employing PVA as a stabilizer, which was successfully loaded into polymeric dissolving MNs. DFS exhibited a 4-fold increase in solubility in DFS-NS compared to that of pure DFS. Moreover, the DFS-NSs exhibited excellent short-term stability and enhanced thermal stability, as confirmed through thermogravimetric analysis (TGA) studies. The mechanical characterization of the DFS-NS loaded ocular microneedles (DFS-NS-OcMNs), revealed that the system was sufficiently strong for effective scleral penetration. Optical coherence tomography (OCT) images confirmed the insertion of 81.23 ± 7.35 % of the total height of the MN arrays into full-thickness porcine sclera. Scleral deposition studies revealed 64 % drug deposition after just 5 min of insertion from DFS-NS-loaded ocular microneedles (OcMNs), which was almost 5 times greater than the deposition from pure DFS-OcMNs. Furthermore, both DFS and DFS-NS-OcMN exhibited remarkable cell viability when evaluated on human retinal pigment (ARPE) cells, suggesting their safety and appropriateness for use in the human eye. Therefore, loading DFS-NS into novel MN devices is a promising technique for effectively delivering DFS to the posterior segment of the eye in a minimally invasive manner.
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How this classification was reachedexpand
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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".