Paper Information

Journal:   NANOMEDICINE JOURNAL   SUMMER 2016 , Volume 3 , Number 3; Page(s) 169 To 178.
 
Paper: 

EVALUATION OF LOADING EFFICIENCY OF AZELAIC ACID-CHITOSAN PARTICLES USING ARTIFICIAL NEURAL NETWORKS

 
 
Author(s):  HANAFI ALI, KAMALI MEHDI, DARVISHI MOHAMMAD HASAN*, AMANI AMIR*
 
* DEPARTMENT OF MEDICAL NANOTECHNOLOGY, SCHOOL OF ADVANCED TECHNOLOGIES IN MEDICINE, TEHRAN UNIVERSITY OF MEDICAL SCIENCES, TEHRAN, IRAN
 
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.

 
Keyword(s): AZELAIC ACID, ARTIFICIAL NEURAL NETWORKS (ANNS), CHITOSAN, LOADING EFFICIENCY
 
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