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Cited by 229

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Physicochemical properties affecting the fate of nanoparticles in pulmonary drug delivery

Liu, Qiaoyu, Guan, Jian, Qin, Lu, Zhang, Xin, Mao, Shirui·2020·Drug Discovery Today

Abstract

The inhaled delivery of nanomedicines has attracted much attention in the treatment of lung diseases or systemic diseases. However, there is a lack of understanding about their fate upon lung delivery. Thus, the objective of this review is to summarize physicochemical properties affecting the fate of nanoparticles after deposition in the lung. First, physiological structure and characteristics of the lung are described. Thereafter, physicochemical properties that could influence the clearance and translocation of nanoparticles in the lung are discussed, including particle size, surface charge and surface hydrophilicity. It is believed that, with a better understanding of the fate of nanoparticles in the lung, it will broaden their application in inhalation for a better therapeutic effect in the future.

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Crossref · 10.1016/j.drudis.2019.09.023

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Metadata

Authors
Liu, Q., Guan, J., Qin, L., Zhang, X., & Mao, S.
Venue
Drug Discovery Today
Publisher
Elsevier BV
Published
2020-01
Volume
25
Issue
1
Pages
150-159
ISSN
1359-6446 (ISSN-L)
OpenAlex
W2979916718
Cited by
229
References
3
FWCI
14.17
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Physicochemical properties affecting the fate of nanoparticles in pulmonary drug delivery. https://app.cochat.ai/papers/10.1016/j.drudis.2019.09.023
The paper
Liu, Q., Guan, J., Qin, L., Zhang, X., & Mao, S. (2020). Physicochemical properties affecting the fate of nanoparticles in pulmonary drug delivery. Drug Discovery Today. https://doi.org/10.1016/j.drudis.2019.09.023

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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.