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采用三水平析因设计制备醋氯芬酸局部生物黏附凝胶

Formulation of topical bioadhesive gel of aceclofenac using 3-level factorial design.

作者信息

Singh Sanjay, Parhi Rabinarayan, Garg Anuj

机构信息

Department of Pharmaceutics, Institute of Technology, Banaras Hindu University, Varanasi, 221005, India.

出版信息

Iran J Pharm Res. 2011 Summer;10(3):435-45.

PMID:24250375
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3813046/
Abstract

The objective of this work was to develop bioadhesive topical gel of Aceclofenac with the help of response-surface approach. Experiments were performed according to a 3-level factorial design to evaluate the effects of two independent variables [amount of Poloxamer 407 (PL-407 = X1) and hydroxypropylmethyl cellulose K100 M (HPMC = X2)] on the bioadhesive character of gel, rheological property of gel (consistency index), and in-vitro drug release. The best model was selected to fit the data. Mathematical equation was generated by Design Expert® software for the model which assists in determining the effect of independent variables. Response surface plots were also generated by the software for analyzing effect of the independent variables on the response. Quadratic model was found to be the best for all the responses. Both independent variable (X1 and X2) were found to have synergistic effect on bioadhesion (Y1) but the effect of HPMC was more pronounced than PL-407. Consistency index was enhanced by increasing the level of both independent variables. An antagonistic effect of both independent variables was found on cumulative percentage release of drug in 2 (Y3) and 8 h (Y4). Both independent variables approximately equally contributed the antagonistic effect on Y3 whereas antagonistic effect of HPMC was more pronounced than PL-407. The effect of formulation variables on the product characteristics can be easily predicted and precisely interpreted by using a 3-level factorial experimental design and generated quadratic mathematical equations.

摘要

本研究的目的是借助响应面法开发醋氯芬酸生物黏附性外用凝胶。根据三水平析因设计进行实验,以评估两个自变量[泊洛沙姆407(PL - 407 = X1)和羟丙基甲基纤维素K100M(HPMC = X2)]对凝胶生物黏附性、凝胶流变学性质(稠度指数)和体外药物释放的影响。选择最佳模型来拟合数据。由Design Expert®软件生成该模型的数学方程,以协助确定自变量的影响。该软件还生成响应面图,用于分析自变量对响应的影响。发现二次模型对所有响应均为最佳。两个自变量(X1和X2)对生物黏附性(Y1)均具有协同作用,但HPMC的作用比PL - 407更显著。通过提高两个自变量的水平可增强稠度指数。发现两个自变量对药物在2小时(Y3)和8小时(Y4)的累积释放百分比具有拮抗作用。两个自变量对Y3的拮抗作用贡献大致相等,而HPMC的拮抗作用比PL - 407更显著。通过使用三水平析因实验设计和生成的二次数学方程,可以轻松预测并精确解释制剂变量对产品特性的影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad08/3813046/bf7f07c18a5f/ijpr-10-435-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad08/3813046/ade8fbbd27da/ijpr-10-435-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad08/3813046/40f7f9f57ae9/ijpr-10-435-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad08/3813046/183a85d7c241/ijpr-10-435-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad08/3813046/bf7f07c18a5f/ijpr-10-435-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad08/3813046/ade8fbbd27da/ijpr-10-435-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad08/3813046/40f7f9f57ae9/ijpr-10-435-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad08/3813046/183a85d7c241/ijpr-10-435-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad08/3813046/bf7f07c18a5f/ijpr-10-435-g004.jpg

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