Deferasirox Nanosuspension Loaded Dissolving Microneedles for Intradermal Delivery
Bibliographic record
Abstract
Microneedles are minimally invasive systems that can deliver drugs intradermally without pain and bleeding and can advantageously replace the hypodermal needles and oral routes of delivery. Deferasirox (DFS) is an iron chelator employed in several ailments where iron overload plays an important role in disease manifestation. In this study, DFS was formulated into a nanosuspension (NSs) through wet media milling employing PVA as a stabilizer and successfully loaded in polymeric dissolving microneedles (DMNs). The release studies for DFS-NS clearly showed a threefold increased dissolution rate compared to pure DFS. The mechanical characterization of DFS-NS-DMNs revealed that the system was sufficiently strong for efficacious skin penetration. Optical coherence tomography images confirmed an insertion of up to 378 µm into full-thickness porcine skin layers. The skin deposition studies showed 60% drug deposition from NS-DMN, which was much higher than from the DFS-NS transdermal patch (DFS-NS-TP) (without needles) or pure DFS-DMNs. Moreover, DFS-NS without DMNs did not deposit well inside the skin, indicating that DMNs played an important role in effectively delivering drugs inside the skin. Therefore, it is evident from the findings that loading DFS-NS into novel DMN devices can effectively deliver DFS transdermally.
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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".