Evaluation of loading efficiency of azelaic acid-chitosan particles using artificial neural networks

• Main Authors: Ali Hanafi, Mehdi Kamali, Mohammad Hasan Darvishi, Amir Amani
• Format: Article
• Language: English
• Published: Mashhad University of Medical Sciences 2016-07-01
• Series: Nanomedicine Journal
• Subjects: Azelaic acid; Artificial neural networks (ANNs); Chitosan; Loading efficiency
• Online Access: http://nmj.mums.ac.ir/article_7022_c9ef40a34527d4d5a3772326d9c23497.pdf

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.