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Cited by 324

The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.

Polymeric microneedles for transdermal protein delivery

Open access
Ye, Yanqi, Yu, Jicheng, Wen, Di, Kahkoska, Anna R., Gu, Zhen·2018·Advanced Drug Delivery Reviews

Abstract

&NA; The intrinsic properties of therapeutic proteins generally present a major impediment for transdermal delivery, including their relatively large molecule size and susceptibility to degradation. One solution is to utilize microneedles (MNs), which are capable of painlessly traversing the stratum corneum and directly translocating protein drugs into the systematic circulation. MNs can be designed to incorporate appropriate structural materials as well as therapeutics or formulations with tailored physicochemical properties. This platform technique has been applied to deliver drugs both locally and systemically in applications ranging from vaccination to diabetes and cancer therapy. This review surveys the current design and use of polymeric MNs for transdermal protein delivery. The clinical potential and future translation of MNs are also discussed. Graphical abstract Figure. No caption available.

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Crossref · 10.1016/j.addr.2018.01.015

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Metadata

Authors
Ye, Y., Yu, J., Wen, D., Kahkoska, A. R., & Gu, Z.
Venue
Advanced Drug Delivery Reviews
Publisher
Elsevier BV
Published
2018-03
Volume
127
Pages
106-118
ISSN
0169-409X (ISSN-L)
OpenAlex
W2793845556
Cited by
324
References
12
FWCI
3.69
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Polymeric microneedles for transdermal protein delivery. https://app.cochat.ai/papers/10.1016/j.addr.2018.01.015
The paper
Ye, Y., Yu, J., Wen, D., Kahkoska, A. R., & Gu, Z. (2018). Polymeric microneedles for transdermal protein delivery. Advanced Drug Delivery Reviews. https://doi.org/10.1016/j.addr.2018.01.015

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.