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Record W4416864568 · doi:10.1021/acsnano.5c05949

Local and Systemic Drug Delivery Using Responsive Microneedles

2025· article· en· W4416864568 on OpenAlexaff
Dutong Liu, Masood Ali, Heather A. E. Benson, Qingsong Ye, Yousuf Mohammed, Dewei Chu, Tushar Kumeria

Bibliographic record

VenueACS Nano · 2025
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicAdvancements in Transdermal Drug Delivery
Canadian institutionsFraser Institute
FundersNational Health and Medical Research CouncilAustralian Research CouncilUniversity of New South WalesRamaciotti Foundations
KeywordsDrug deliveryDrugTargeted drug deliveryDrug administrationSystemic administrationDrug carrier

Abstract

fetched live from OpenAlex

Microneedles (μNDs) have emerged as promising minimally invasive drug delivery systems, offering advantages such as painless administration and enhanced drug permeability. Among various μNDs technologies, responsive μNDs have attracted growing attention for their ability to react to physiological or external stimuli, allowing precise and on-demand drug release for both localized and systemic therapies. This review explores the recent advancements in responsive μNDs triggered by various endogenous and exogenous signals that correspond to specific targeted diseases and/or sites of application. Additionally, the review highlights the challenges associated with scalability, biocompatibility, and regulatory approval of responsive μNDs and provides insights into future directions for clinical translation. By consolidating the latest developments, this review aims to support the design and optimization of next-generation smart drug delivery systems.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.127
Threshold uncertainty score0.890

Codex and Gemma teacher scores by category

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

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 head0.054
GPT teacher head0.398
Teacher spread0.344 · 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 teacher head, not a consensus.

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

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

Citations7
Published2025
Admission routes1
Has abstractyes

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