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Record W3102615690 · doi:10.1016/j.jddst.2020.102192

Characterization method for calculating diffusion coefficient of drug from polylactic acid (PLA) microneedles into the skin

2020· article· en· W3102615690 on OpenAlexafffund
Libo Wu, Pranav Shrestha, Martina Iapichino, Yicheng Cai, Beomjoon Kim, Boris Stoeber

Bibliographic record

VenueJournal of Drug Delivery Science and Technology · 2020
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicAdvancements in Transdermal Drug Delivery
Canadian institutionsUniversity of British Columbia
FundersUniversity of British ColumbiaUniversity of Tokyo
KeywordsMaterials scienceStratum corneumBiomedical engineeringPolylactic acidDermisHypodermic needleDrug deliveryTransdermalRhodamine BNanotechnologyComposite materialPolymerPharmacologyPathologyChemistryMedicine

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.035
GPT teacher head0.367
Teacher spread0.332 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreMethods

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".

Quick stats

Citations51
Published2020
Admission routes2
Has abstractyes

Explore more

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