Affiliation:
1. Organosilicon Research Laboratory, Faculty of Chemistry, University of Tabriz, Tabriz 51666-14766, Iran
2. Medicinal
Plants Research Center, Institute of Medicinal Plants, ACECR, Karaj, Iran
Abstract
Background:
Silymarin is a flavonolignan extracted from Silybum marianum with various
therapeutic applications. Many studies have focused on improving the bioavailability of silymarin
due to its wide range of efficacy and low bioavailability. Chitosan, a naturally occurring
polymeric substance, has a strong reputation for increasing the solubility of poorly soluble compounds.
Objective:
This study used artificial neural networks (ANNs) to measure the effects of pH, chitosan
to silymarin ratio, chitosan to tripolyphosphate ratio, and stirring time on the loading efficiency
of silymarin into chitosan particles.
Methods:
A model was developed to investigate the interactions between input factors and silymarin
loading efficiency. The DPPH method was utilized to determine the antioxidant activity of
an optimized formula and pure raw materials.
Results:
According to the outcome of the ANN model, pH and the chitosan to silymarin ratio
demonstrated significant effects on loading efficiency. In addition, increased stirring time decreased
silymarin loading, whereas the chitosan-to-tripolyphosphate ratio showed a negligible effect
on loading efficiency.
Conclusion:
Maximum loading efficiency occurred at a pH of approximately~5. Moreover, silymarin-
loaded chitosan particles with a lower IC50 value (36.17 ± 0.02 ppm) than pure silymarin
(165.04 ± 0.07 ppm) demonstrated greater antioxidant activity.
Funder
Office of Postgraduate Studies of the University of Tabriz
Publisher
Bentham Science Publishers Ltd.
Subject
Drug Discovery,Molecular Medicine,General Medicine