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引用本文:张胜,李田田,瞿海斌.基于蒙特卡洛的中美药典含量均匀度检查法的比较研究[J].中国现代应用药学,2019,36(19):2405-2410.
ZHANG Sheng,LI Tiantian,QU Haibin.Comparison Study of the Content Uniformity Tests in Chinese Pharmacopoeia and United States Pharmacopeia Based on Monte Carlo Simulation[J].Chin J Mod Appl Pharm(中国现代应用药学),2019,36(19):2405-2410.
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基于蒙特卡洛的中美药典含量均匀度检查法的比较研究
张胜1, 李田田2, 瞿海斌1
1.浙江大学药学院, 杭州 310058;2.浙江大学医学院附属妇产科医院, 杭州 310006
摘要:
目的 利用蒙特卡洛方法比较研究中国药典和美国药典的含量均匀度检查法,并提出改进思路。方法 以含量均匀度检查法准确率为性能指标,采用蒙特卡洛方法模拟药品质量的变化,并进行模拟抽样检查,比较中美药典含量均匀度检查法的性能;通过中心复合实验设计,考察中美药典含量均匀度检查法的检查参数对准确率的影响。结果 在不同均值和标准差情况下,中美药典的检查准确率无显著差异;中心复合实验设计的结果表明,中美药典含量均匀度检查法的参数均可进一步优化,从而提高检查准确率。结论 中美药典含量均匀度检查法的准确率基本一致,提出了优化含量均匀度检查参数的新思路。
关键词:  含量均匀度检查法  准确率  蒙特卡洛  实验设计  参数优化
DOI:10.13748/j.cnki.issn1007-7693.2019.19.008
分类号:R917.4
基金项目:浙江省科技计划项目(2018C03075)
Comparison Study of the Content Uniformity Tests in Chinese Pharmacopoeia and United States Pharmacopeia Based on Monte Carlo Simulation
ZHANG Sheng1, LI Tiantian2, QU Haibin1
1.College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China;2.Women's Hospital, School of Medicine, Zhejiang University, Hangzhou 310006, China
Abstract:
OBJECTIVE To study the performance of the content uniformity(CU) tests in the Chinese Pharmacopoeia(ChP) and the United States Pharmacopeia(USP) and provide ideas to improve the performance of the tests. METHODS Monte Carlo method was applied to simulate the drug product quality as well as the sampling process. The accuracies of CU tests in ChP and USP were compared as the performance index; the effects of parameters on the accuracies were studied through the central composite design(CCD) experiments. RESULTS There was no significant difference between the accuracies of CU tests in ChP and USP; the results of CCD experiments showed that parameters of the CU tests in both ChP and USP could be further optimized to improve accuracies. CONCLUSION The accuracies of CU tests in ChP and USP is basically the same and new ideas to optimize the parameters of CU tests are provided.
Key words:  content uniformity test  accuracy  Monte Carlo  design of experiments  parameter optimization
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