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In situ forming hydrogels based on chitosan for drug delivery and tissue regeneration

Open access
Liu, Li, Gao, Qi, Lu, Xuemin, Zhou, Huifang·2016·Asian Journal of Pharmaceutical Sciences

Abstract

In situ forming hydrogels with simple sol–gel transition are more practicable as injectable hydrogels for drug delivery and tissue regeneration. State-of-the-art in situ gelling systems can easily and efficiently be formed by different mechanisms in situ. Chitosan is a kind of natural polysaccharide that is widely exploited for biomedical applications due to its good biocompatibility, low immunogenicity and specific biological activities. Chitosan-based in situ gelling systems have already gained much attention as smart biomaterials in the development of several biomedical applications, such as for drug delivery systems and regeneration medicine. Herein, we review the typical in situ gelling systems based on chitosan and mechanisms involved in hydrogel forming, and report advances of chitosan-based in situ gels for the applications in drug delivery and tissue regeneration. Finally, development prospects of in situ forming hydrogels based on chitosan are also discussed in brief.

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Metadata

Authors
Liu, L., Gao, Q., Lu, X., & Zhou, H.
Venue
Asian Journal of Pharmaceutical Sciences
Publisher
Elsevier BV
Published
2016-12
Volume
11
Issue
6
Pages
673-683
ISSN
1818-0876 (ISSN-L)
OpenAlex
W2469037914
Cited by
232
References
0
FWCI
9.22
Type
journal article
Language
en
Open access
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CoChat. (2026). Citation check: In situ forming hydrogels based on chitosan for drug delivery and tissue regeneration. https://app.cochat.ai/papers/10.1016/j.ajps.2016.07.001
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Liu, L., Gao, Q., Lu, X., & Zhou, H. (2016). In situ forming hydrogels based on chitosan for drug delivery and tissue regeneration. Asian Journal of Pharmaceutical Sciences. https://doi.org/10.1016/j.ajps.2016.07.001

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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.