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Cited by 184

The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.

Delivery of oligonucleotides with lipid nanoparticles

Open access
Wang, Yuhua, Miao, Lei, Satterlee, Andrew, Huang, Leaf·2015·Advanced Drug Delivery Reviews

Abstract

Since their inception in the 1980's, oligonucleotide-based (ON-based) therapeutics have been recognized as powerful tools that can treat a broad spectrum of diseases. The discoveries of novel regulatory methods of gene expression with diverse mechanisms of action are still driving the development of novel ON-based therapeutics. Difficulties in the delivery of this class of therapeutics hinder their in vivo applications, which forces drug delivery systems to be a prerequisite for clinical translation. This review discusses the strategy of using lipid nanoparticles as carriers to deliver therapeutic ONs to target cells in vitro and in vivo. A discourse on how chemical and physical properties of the lipid materials could be utilized during formulation and the resulting effects on delivery efficiency constitutes the major part of this review.

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Crossref · 10.1016/j.addr.2015.02.007

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Metadata

Authors
Wang, Y., Miao, L., Satterlee, A., & Huang, L.
Venue
Advanced Drug Delivery Reviews
Publisher
Elsevier BV
Published
2015-06
Volume
87
Pages
68-80
ISSN
0169-409X (ISSN-L)
OpenAlex
W2071481518
Cited by
184
References
10
FWCI
1.49
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Delivery of oligonucleotides with lipid nanoparticles. https://app.cochat.ai/papers/10.1016/j.addr.2015.02.007
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Wang, Y., Miao, L., Satterlee, A., & Huang, L. (2015). Delivery of oligonucleotides with lipid nanoparticles. Advanced Drug Delivery Reviews. https://doi.org/10.1016/j.addr.2015.02.007

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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.