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Lipid-Based Nanoparticles in The Systemic Delivery of siRNA

Authors: Qiaoya, Lin; Juan, Chen; Zhihong, Zhang; Gang, Zheng;

Lipid-Based Nanoparticles in The Systemic Delivery of siRNA

Abstract

RNAi therapeutics are believed to be the future of personalized medicine and have shown promise in early clinical trials. However, many physiological barriers exist in the systemic delivery of siRNAs to the cytoplasm of targeted cells to perform their function. To overcome these barriers, many siRNA delivery systems have been developed. Among these, lipid-based nanoparticles have great potential owing to their biocompatibility and low toxicity in comparison with inorganic nanoparticles and viral systems. This review discusses the hurdles of systemic siRNA delivery and highlights the recent progress made in lipid-based nanoparticles, which are categorized based on their key lipid components, including cationic lipid, lipoprotein, lipidoid, neutral lipid and anionic lipid-based nanoparticles. It is expected that these lipid nanoparticle-based siRNA delivery systems will have an enabling role for personalized cancer medicine, where siRNA delivery will join forces with genetic profiling of individual patients to achieve the best treatment outcome.

Keywords

Treatment Outcome, Neoplasms, Gene Transfer Techniques, Humans, Nanoparticles, Genetic Therapy, RNA, Small Interfering, Lipids

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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
121
Top 1%
Top 10%
Top 1%
Related to Research communities
Cancer Research
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