Synthesis and characterization of low-toxic amphiphilic chitosan derivatives and their application as micelle carrier for antitumor drug

Huo, Meirong; Zhang, Yong; Zhou, Jianping; Zou, Aifeng; Yu, Di; Wu, Yiping; Li, Jing; Li, Hong

doi:10.1016/j.ijpharm.2010.05.001

Cited by 155 publications

(99 citation statements)

References 61 publications

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“…As the description in Figure 2, the positions of the peaks in the spectra are basically consistent with the report in the literature [14]. For the spectra of CS, the distribution of peaks is as follow: 1.8(CH 3 ), 4.3(H1), 2.9(H2), 3.3-3.9 (H3, H4, H5, H6).…”

Section: B Nmrsupporting

confidence: 89%

Synthesis of N-alkylated Chitosan and its Aggregation Behavior

Zhang¹,

Deng²,

Guan³

et al. 2018

Proceedings of the 4th Annual International Conference on Material Engineering and Application (ICMEA 2017)

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Section: B Nmrsupporting

confidence: 89%

Synthesis of N-alkylated Chitosan and its Aggregation Behavior

Zhang¹,

Deng²,

Guan³

et al. 2018

Proceedings of the 4th Annual International Conference on Material Engineering and Application (ICMEA 2017)

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“…The antitumor drug cisplatin was encapsulated into the hydrophobic core with a drug loading of 80%. 28 The amphiphilic derivatives of N-octyl-O, N-carboxymethyl chitosan (OCC) prepared by Huo et al 28 enhanced the solubility of the insoluble antitumor drug paclitaxel. Solubility of paclitaxel was improved nearly 500-fold with a drug loading of 34.6% and encapsulation rate of 89.9%, indicating that OCC is a potentially excellent solubilization carrier for insoluble drugs.…”

Section: Self-assemblymentioning

confidence: 99%

“…73 The combination of bioadhesion and paracellular transport effects has led to chitosan to be considered for the delivery of estradiol via the nasal cavity. Huo et al, 74 who used N-octyl-O-glycol chitosan (OGC) as the carrier of paclitaxel for intravenous administration, found that OGC for intravenous administration had good biocompatibility and no toxicity. Moreover, paclitaxel-loaded OGC micelles had low toxicity and a higher tolerated dose.…”

Section: Routes Of Administrationmentioning

confidence: 99%

Recent advances of chitosan nanoparticles as drug carriers

Zeng¹

2011

IJN

258

124

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Chitosan nanoparticles are good drug carriers because of their good biocompatibility and biodegradability, and can be readily modified. As a new drug delivery system, they have attracted increasing attention for their wide applications in, for example, loading protein drugs, gene drugs, and anticancer chemical drugs, and via various routes of administration including oral, nasal, intravenous, and ocular. This paper reviews published research on chitosan nanoparticles, including its preparation methods, characteristics, modification, in vivo metabolic processes, and applications.

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“…For instance, studies have shown that vehicles can be selected to improve the solubility and/or permeability of a drug or to target the drug to a specific disease site (Loftsson 1998;Porter et al 2007;Shin et al 2009;Hans and Lowman 2002;Liu et al 2011;Lee et al 2003). Vehicles have also been designed and formulated to mitigate unwanted toxicities associated with drugs that are considered highly toxic (Huo et al 2010;Uchino et al 2005;Kelava et al 2010). Vehicles offer toxicity relief in several ways.…”

Section: Introductionmentioning

confidence: 99%

Using random forest and decision tree models for a new vehicle prediction approach in computational toxicology

et al. 2015

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Drug vehicles are chemical carriers that provide beneficial aid to the drugs they bear. Taking advantage of their favourable properties can potentially allow the safer use of drugs that are considered highly toxic. A means for vehicle selection without experimental trial would therefore be of benefit in saving time and money for the industry. Although machine learning is increasingly used in predictive toxicology, to our knowledge there is no reported work in using machine learning techniques to model drug-vehicle relationships for vehicle selection to minimise toxicity. In this paper we demonstrate the use of data mining and machine learning techniques to process, extract and build models based on classifiers (decision trees and random forests) that allow us to predict which vehicle would be most suited to reduce a drug's toxicity. Using data acquired from the National Institute of Health's (NIH) Developmental Therapeutics Program (DTP) we propose a methodology using an area under a curve (AUC) approach that allows us to distinguish which vehicle provides the best toxicity profile for a drug and build classification models based on this knowledge. Our results show that we can achieve prediction accuracies of 80 % using random forest models whilst the decision tree models produce Communicated by D. Neagu. Electronic supplementary materialThe online version of this article (doi:10.1007/s00500-015-1925-9) contains supplementary material, which is available to authorized users.

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Synthesis and characterization of low-toxic amphiphilic chitosan derivatives and their application as micelle carrier for antitumor drug

Cited by 155 publications

References 61 publications

Synthesis of N-alkylated Chitosan and its Aggregation Behavior

Synthesis of N-alkylated Chitosan and its Aggregation Behavior

Recent advances of chitosan nanoparticles as drug carriers

Using random forest and decision tree models for a new vehicle prediction approach in computational toxicology

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