evaluation of loading efficiency of azelaic acid-chitosan particles using artificial neural networks
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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.
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Journal title:
nanomedicine journalجلد ۳، شماره ۳، صفحات ۱۶۹-۱۷۸
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