Controlled Transdermal Iontophoresis of Insulin from Water-Soluble Polypyrrole Nanoparticles: An In Vitro Study
Bibliographic record
Abstract
The iontophoresis delivery of insulin (INS) remains a serious challenge due to the low permeability of the drug through the skin. This work aims to investigate the potential of water-soluble polypyrrole nanoparticles (WS-PPyNPs) as a drug donor matrix for controlled transdermal iontophoresis of INS. WS-PPyNPs have been prepared via a simple chemical polymerization in the presence of sodium dodecyl sulfate (SDS) as both dopant and the stabilizing agent. The synthesis of the soluble polymer was characterized using field emission scanning electron microscopy (FESEM), dynamic light scattering (DLS), fluorescence spectroscopy, and Fourier transform infrared (FT–IR) spectroscopy. The loading mechanism of INS onto the WS-PPyNPs is based on the fact that the drug molecules can be replaced with doped dodecyl sulfate. A two-compartment Franz-type diffusion cell was employed to study the effect of current density, formulation pH, INS concentration, and sodium chloride concentration on anodal iontophoresis (AIP) and cathodal iontophoresis (CIP) of INS across the rat skin. Both AIP and CIP delivery of INS using WS-PPyNPs were significantly increased compared to passive delivery. Furthermore, while the AIP experiment (60 min at 0.13 mA cm–2) show low cumulative drug permeation for INS (about 20.48 µg cm−2); the CIP stimulation exhibited a cumulative drug permeation of 68.29 µg cm−2. This improvement is due to the separation of positively charged WS-PPyNPs and negatively charged INS that has occurred in the presence of cathodal stimulation. The obtained results confirm the potential applicability of WS-PPyNPs as an effective approach in the development of controlled transdermal iontophoresis of INS.
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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 | 0.000 |
| Open science | 0.001 | 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 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".