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

Document Type : Research Paper


1 Nanobiotechology Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran

2 Department of Medical Nanotechnology, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran

3 Medical Biomaterials Research Center, Tehran University of Medical Sciences, Tehran, Iran


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.


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