Optimization of Paeoniae Radix Alba and Glycyrrhiza umbilical patches prescription by Box-Behnken response surface method combined with GA-BP neural network based on CRITIC method weighting
Objective:To optimize the prescription of Paeoniae Radix Alba and Glycyrrhiza umbilical patches(referred to as umbilical patches).Methods:Sing transdermal penetration test in vitro and high performance liquid chromatography(HPLC)with the appearance,cumulative release of 8 indicator ingredients and that of total ingredients as evaluation indexes and optimizing the drug loading,penetration enhancer dosage and the ratio of PEG6000 and PEG4000 to micro-powder silica gel by single factor test and Box-Behnken response surface method combined with GA-BP neural network to determine the best prescription.Results:The comprehensive evaluation indexes of Box-Behnken response surface method and GA-BP neural network optimization were 1.2808(n=3,RSD=3.05%)and 1.1937(n=3,RSD=2.26%),respectively.After comparison and verification,the optimal prescription process for Paeoniae Radix Alba and Glycyrrhiza was 9.71%of micro-powder silica gel to PEG,24.56%of drug loading and 2.87%of penetration enhancer.Conclusion:The optimal prescription of umbilical patches was determined by Box-Behnken response surface test combined GA-BP neural network.The umbilical patches prepared by this prescription have moderate softness and hardness,and good skin permeability.
Paeoniae Radix Alba and Glycyrrhiza umbilical patchestransdermal penetration test in vitroCRITIC methodBox-Behnken response surfaceGA-BP neural network
万方数据
维普
