MétaCan
Menu
Back to cohort
Record W4393018337 · doi:10.3389/jpps.2024.12434

Recent progress of polymeric microneedle-assisted long-acting transdermal drug delivery

2024· review· en· W4393018337 on OpenAlexvenueno aff
Fanda Meng, Xinyu Qiao, Chenglong Xin, Xiaoli Ju, Meilin He

Bibliographic record

VenueJournal of Pharmacy & Pharmaceutical Sciences · 2024
Typereview
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicAdvancements in Transdermal Drug Delivery
Canadian institutionsnot available
FundersShandong Academy of Medical SciencesShandong First Medical UniversityNatural Science Foundation of Shandong Province
KeywordsTransdermalStratum corneumNanotechnologyDrug deliveryPatient complianceMedicineRisk analysis (engineering)Materials sciencePharmacology

Abstract

fetched live from OpenAlex

Microneedle (MN)-assisted drug delivery technology has gained increasing attention over the past two decades. Its advantages of self-management and being minimally invasive could allow this technology to be an alternative to hypodermic needles. MNs can penetrate the stratum corneum and deliver active ingredients to the body through the dermal tissue in a controlled and sustained release. Long-acting polymeric MNs can reduce administration frequency to improve patient compliance and therapeutic outcomes, especially in the management of chronic diseases. In addition, long-acting MNs could avoid gastrointestinal reactions and reduce side effects, which has potential value for clinical application. In this paper, advances in design strategies and applications of long-acting polymeric MNs are reviewed. We also discuss the challenges in scale manufacture and regulations of polymeric MN systems. These two aspects will accelerate the effective clinical translation of MN products.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.283
GPT teacher head0.539
Teacher spread0.256 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations24
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Pharmacy & Pharmaceutical SciencesSame topicAdvancements in Transdermal Drug DeliveryFrench-language works237,207