Title of article :
Evaluation of loading efficiency of azelaic acid-chitosan particles using artificial neural networks
Author/Authors :
-، - نويسنده Nanobiotechology Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran Hanafi, Ali , -، - نويسنده Nanobiotechology Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran Kamali, Mehdi , -، - نويسنده Nanobiotechology Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran Darvishi, Mohammad Hasan , -، - نويسنده Department of Medical Nanotechnology, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran|Medical Biomaterials Research Center, Tehran University of Medical Sciences, Tehran, Iran Amani, Amir
Issue Information :
فصلنامه با شماره پیاپی 0 سال 2016
Pages :
10
From page :
169
To page :
178
Abstract :
-
Abstract :
Objective(s): Chitosan, a biodegradable and cationic polysaccharide with increasing applications in biomedicine, possesses many advantages including mucoadhesivity, biocompatibility, and low-immunogenicity. The aim of this study, was investigating the influence of pH, ratio of azelaic acid/chitosan and molecular weight of chitosan on loading efficiency of azelaic acid in chitosan particles. Materials and Methods:  A model was generated using artificial neural networks (ANNs) to study interactions between the inputs and their effects on loading of azelaic acid. Results: From the details of the model, pH showed a reverse effect on the loading efficiency. Also, a certain ratio of drug/chitosan (~ 0.7) provided minimum loading efficiency, while molecular weight of chitosan showed no important effect on loading efficiency.Conclusion: In general, pH and drug/chitosan ratio indicated an effect on loading of the drug. pH was the major factor affecting in determining loading efficiency.
Journal title :
Nanomedicine Journal
Serial Year :
2016
Journal title :
Nanomedicine Journal
Record number :
2397514
Link To Document :
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