(2016) Evaluation of loading efficiency of azelaic acid-chitosan particles using artificial neural networks. Nanomedicine Journal. pp. 169-178. ISSN 2322-3049
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Evaluation of loading efficiency of azelaic acid-chitosan particles using artificial neural networks.pdf Download (3MB) |
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 (similar to 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.
Item Type: | Article |
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Keywords: | Azelaic acid Artificial neural networks (ANNs) Chitosan Loading efficiency Science & Technology - Other Topics |
Divisions: | |
Page Range: | pp. 169-178 |
Journal or Publication Title: | Nanomedicine Journal |
Journal Index: | ISI |
Volume: | 3 |
Number: | 3 |
Identification Number: | https://doi.org/10.7508/nmj.2016.03.004 |
ISSN: | 2322-3049 |
Depositing User: | مهندس مهدی شریفی |
URI: | http://eprints.bmsu.ac.ir/id/eprint/5007 |
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