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

Authors

ali hanafi nanobiotechology research center, baqiyatallah university of medical sciences, tehran, iranسازمان اصلی تایید شده: دانشگاه علوم پزشکی بقیه الله (baqiyatallah university of medical sciences)

mehdi kamali nanobiotechology research center, baqiyatallah university of medical sciences, tehran, iranسازمان اصلی تایید شده: دانشگاه علوم پزشکی بقیه الله (baqiyatallah university of medical sciences)

mohammad hasan darvishi nanobiotechology research center, baqiyatallah university of medical sciences, tehran, iranسازمان اصلی تایید شده: دانشگاه علوم پزشکی بقیه الله (baqiyatallah university of medical sciences)

amir amani 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.

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Journal title:
nanomedicine journal

جلد ۳، شماره ۳، صفحات ۱۶۹-۱۷۸

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