Development of Norelgestromin Dissolving Bilayer Microarray Patches for Sustained Release of Hormonal Contraceptive
Bibliographic record
Abstract
Microarray patches (MAPs) offer a noninvasive and patient-friendly drug delivery method, suitable for self-administration, which is especially promising for low- and middle-income country settings. This study focuses on the development of dissolving bilayer MAPs loaded with norelgestromin (NGMN) as a first step towards developing a future potential drug delivery system for sustained hormonal contraception. The fabricated MAPs were designed with the appropriate needle lengths to penetrate the stratum corneum, while remaining minimally stimulating to dermal nociceptors. Ex vivo assessments showed that the MAPs delivered an average of 176 ± 60.9 μg of NGMN per MAP into excised neonatal porcine skin, representing 15.3 ± 5.3% of the loaded drug. In vivo pharmacokinetic analysis in Sprague Dawley rats demonstrated a Tmax of 4 h and a Cmax of 67.4 ± 20.1 ng/mL for the MAP-treated group, compared to a Tmax of 1 h and a Cmax of 700 ± 138 ng/mL for the intramuscular (IM) injection group, with a relative bioavailability of approximately 10% for the MAPs. The MAP-treated rats maintained plasma levels sufficient for therapeutic effects for up to 7 days after a single application. These results indicate the potential of NGMN-loaded dissolving bilayer MAPs, with further development focused on extending the release duration and improving bioavailability for prolonged contraceptive effects.
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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".