Characterization method for calculating diffusion coefficient of drug from polylactic acid (PLA) microneedles into the skin
Bibliographic record
Abstract
Microneedles are designed for piercing the stratum corneum and delivering drugs into the epidermis and dermis layers of the skin. Their micrometric dimension causes minor or negligible stimulations to sensory nerve fibers in the dermis layer of the skin, making drug administration through microneedles less painful compared to conventional hypodermic needle injection. With the advancement of microneedle related research, an increasing number of drugs are using microneedle-mediated drug delivery in the topical area of the skin, including localized delivery of some highly toxic drugs. It is essential to understand drug diffusion from microneedles to skin to avoid unwanted spread of toxic drugs in non-infected areas. This work aims to 1) deliver into the skin tissue fluorescent rhodamine B as a model drug from coated polylactic acid (PLA) microneedles and dissolvable microneedles; 2) detect and depict the concentration distribution of the model drug from two types of microneedles into the skin tissue respectively; 3) determine a reliable diffusion coefficient of the model drug based on a constant source diffusion model and a limited source diffusion model for dissolvable microneedles and coated PLA microneedles, respectively. Dissolvable microneedles and coated PLA microneedles were designed and fabricated by a novel methodology combining 3D printing, chemical etching, micro-molding and drop coating. Rhodamine B was chosen as the model drug to enable fluorescent detection. Two types of microneedles were mounted to a single patch and inserted into porcine skin to deliver the model drug. After microneedle removal, confocal microscopy was used to monitor the fluorescence intensity of rhodamine B in the skin tissue. Based on an intensity-concentration calibration and two diffusion models, the diffusion coefficients of rhodamine B from the constant source (dissolvable microneedles) and limited source (coated PLA microneedles) to the dermis layer of porcine skin were inferred to be from 3.1×10−8 to 3.6×10−8 cm2/s. This characterization method is expected to offer medical personnel a quantitative understanding of the diffusion process related to microneedle-mediated transdermal drug delivery.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".