Dacarbazine-loaded Bilayer Dissolving Microneedle Array Patch for Localized Delivery in Cutaneous Melanoma
Bibliographic record
Abstract
Melanoma is a highly aggressive skin cancer that accounts for only ~ 1% of all skin cancer cases but is responsible for most skin cancer-related deaths. Despite advances in systemic therapies, localized treatment options remain limited. Dacarbazine (DCB), the only FDA-approved chemotherapeutic agent for melanoma, is administered intravenously and is associated with systemic toxicity, poor patient compliance, and nonspecific drug distribution. This study presents a bilayer dissolving microneedle array patch (dMAP) for localized, minimally invasive delivery of DCB to the skin, offering a potential alternative for treating cutaneous melanoma. The tip-casting gel formulation was optimized to ensure sharp, defect-free MAP tips with uniform drug distribution. The optimized bilayer dMAP exhibited strong mechanical properties (< 10% needle deformation) and effective insertion capability, reaching approximately 390 µm in depth within the Parafilm® M model. Ex vivo evaluations using full-thickness neonatal porcine skin demonstrated the complete dissolution of bilayer dMAP tips within 60 min and effective pore formation, as confirmed by methylene blue staining. In ex vivo setup, the bilayer dMAP formulation demonstrated 3.93-fold increase in permeability and a 3.02-fold increase in DCB deposition compared with those of the suspension. Furthermore, bilayer dMAP maintained complete drug stability over 8 days at room temperature under light-protected conditions, whereas free DCB showed approximately 7.5% degradation in aqueous media over the same duration. Therefore, bilayer dMAP provides a stable, minimally invasive, and efficient platform for localized drug delivery to the skin, highlighting its potential as a promising alternative to conventional topical formulations for the treatment of cutaneous melanoma.
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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".