统计过程控制结合近红外光谱在栀子中间体纯化工艺过程批放行中的应用研究
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摘要
目的采用统计过程控制方法建立热毒宁注射液栀子中间体纯化工艺过程批放行标准,保证批间质量的均一性和稳定性。方法收集48批栀子中间体纯化溶液作为训练集样本,测定绿原酸、山栀苷、京尼平苷酸、去乙酰车叶草酸甲酯、京尼平龙胆双糖苷、栀子苷和总酸的量;建立定量放行标准,扫描样本近红外光谱(NIRS),建立基于光谱信息的定性放行标准。应用Box-Behnken实验设计制备不同工艺条件下的17批栀子中间体纯化溶液作为验证集,验证建立的定量标准和定性标准的可行性。结果建立的定量放行范围为绿原酸5.753~6.713 mg/g、山栀苷9.456~10.723 mg/g、京尼平苷酸3.313~4.401 mg/g、去乙酰车叶草酸甲酯15.260~16.419 mg/g、京尼平龙胆双糖苷30.529~33.473 mg/g、栀子苷165.17~175.16 mg/g和总酸45.028~53.118 mg/g;建立的NIRS定性放行限为Hotelling T2=4.067 8,DMod X=1.218 8。验证集中只有第1、5、7、9、10、14、15、16、17批的样本各成分的量均在定量放行控制限范围内,NIRS信息也在定性放行控制限范围内。结论运用NIRS和统计过程控制技术相结合,建立批放行定量和定性标准,简单可行,可用于栀子中间体纯化工艺过程质量控制。
Objective To establish the batch release criteria of Gardenia jasminoides intermediate purification process based on statistical process control technology in order to ensure the batch-to-batch consistency and stability. Methods Forty-eight batches of G. jasminoides intermediate purified solution were collected as the calibration set. The content of chlorogenic acid,shanzhiside,geniposidic acid,deacetyl asperulosidic acid methyl ester,genipin-1-β-D-gentiobioside,geniposide,and total acid were determined to establish the quantitative release criteria. Near-infrared spectra(NIRS) were acquired to establish the qualitative release criteria. Seventeen batches of G. jasminoides intermediate purified solution were prepared under different process conditions by the Box-Behnken experimental design. They were regarded as the validation set to verify the feasibility of the established quantitative and qualitative release criteria. Results The established quantitative release ranges were: chlorogenic acid 5.753—6.713 mg/g,shanzhiside 9.456—10.723 mg/g,geniposidic acid 3.313—4.401 mg/g,deacetyl asperulosidic acid methyl ester 15.260—16.419 mg/g,genipin-1-β-D-gentiobioside 30.529 — 33.473 mg/g,geniposide 165.17 — 175.16 mg/g,and total acid 45.028 — 53.118 mg/g,respectively. The established qualitative release upper limits were: Hotelling T2 = 4.067 8 and DMod X = 1.218 8. For sample 1,5,7,9,10,14—17 from the validation set,the content of quality control indicators satisfied the quantitative release criteria and NIRS satisfied the qualitative release criteria. Conclusion Based on NIRS and statistical process control technology,the developed quantitative and qualitative release criteria are simple and feasible. They could be used for the production quality control of G. jasminoides intermediate purification process.
Objective To establish the batch release criteria of Gardenia jasminoides intermediate purification process based on statistical process control technology in order to ensure the batch-to-batch consistency and stability. Methods Forty-eight batches of G. jasminoides intermediate purified solution were collected as the calibration set. The content of chlorogenic acid,shanzhiside,geniposidic acid,deacetyl asperulosidic acid methyl ester,genipin-1-β-D-gentiobioside,geniposide,and total acid were determined to establish the quantitative release criteria. Near-infrared spectra(NIRS) were acquired to establish the qualitative release criteria. Seventeen batches of G. jasminoides intermediate purified solution were prepared under different process conditions by the Box-Behnken experimental design. They were regarded as the validation set to verify the feasibility of the established quantitative and qualitative release criteria. Results The established quantitative release ranges were: chlorogenic acid 5.753—6.713 mg/g,shanzhiside 9.456—10.723 mg/g,geniposidic acid 3.313—4.401 mg/g,deacetyl asperulosidic acid methyl ester 15.260—16.419 mg/g,genipin-1-β-D-gentiobioside 30.529 — 33.473 mg/g,geniposide 165.17 — 175.16 mg/g,and total acid 45.028 — 53.118 mg/g,respectively. The established qualitative release upper limits were: Hotelling T2 = 4.067 8 and DMod X = 1.218 8. For sample 1,5,7,9,10,14—17 from the validation set,the content of quality control indicators satisfied the quantitative release criteria and NIRS satisfied the qualitative release criteria. Conclusion Based on NIRS and statistical process control technology,the developed quantitative and qualitative release criteria are simple and feasible. They could be used for the production quality control of G. jasminoides intermediate purification process.
引文
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[13]吴莎,刘启安,李云,等.最小二乘支持向量机和偏最小二乘法在栀子中间体纯化工艺近红外定量分析中的应用[J].中草药,2015,46(7):990-997.
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[19]徐冰,罗赣,林兆洲,等.基于过程分析技术和设计空间的金银花醇沉加醇过程终点检测[J].高等学校化学学报,2013,34(10):2284-2289.
[2]冯雄峰,阳宪惠,徐用懋.多元统计过程控制方法的平方预测误差分析[J].清华大学学报,1999,39(7):41-45.
[3]栾郭宏,贺凯讯,程辉,等.基于神经网络的近红外光谱辛烷值模型的研究及应用[J].计算机与应用化学,2014,31(1):63-69.
[4]周海燕,徐冰,史新元,等.清开灵注射液中金银花液生产工艺多元统计过程监控研究[J].世界科学技术—中医药现代化,2012,14(4):1877-1883.
[5]杨哲萱,周立红,章顺楠,等.NIRS技术在中药生产中的应用及其验证方法探讨[J].中草药,2013,44(10):1342-1348.
[6]王多加,周向阳,金同铭,等.近红外光谱检测技术在农业和食品分析上的应用[J].光谱学与光谱分析,2004,24(4):447-450.
[7]杜文俊,刘雪松,陶玲艳,等.热毒宁注射液金银花和青蒿(金青)醇沉过程中多指标的近红外快速检测[J].中草药,2015,46(1):61-66.
[8]曲佳,王秋珍,王杰.近红外光谱法快速鉴别不同厂家的天王补心丸(小蜜丸)[J].药物评价研究,2014,37(4):346-348.
[9]Lieftucht D,Kruger U,Irwin G W.Improved reliability in diagnosing faults using multivariate statistics[J].Comput Chem Eng,2006,30(5):901-912.
[10]孙文爽,陈兰祥.多元统计分析[M].北京:高等教育出版社,1994.
[11]陈亚华,王树青.用数据驱动实现的抗生素发酵过程监控软件[J].计算机工程与应用,2004,40(29):223-225.
[12]王家俊,袁洪福,陈剑明.多变量分析方法结合近红外光谱表征卷烟配方的过程质量[J].烟草科技,2006(10):5-9.
[13]吴莎,刘启安,李云,等.最小二乘支持向量机和偏最小二乘法在栀子中间体纯化工艺近红外定量分析中的应用[J].中草药,2015,46(7):990-997.
[14]王毅,马翔,温亚东,等.近红外光谱与多元统计方法用于生产过程实时分析[J].光谱学与光谱分析,2013,33(5):1226-1229.
[15]EI-Midany T T,EI-Baz M A,Abd-Elwahed M S.A proposed framework for control chart pattern recognition in multivariate process using artificial neural networks[J].Expert Syst Appl,2010,37(2):1035-1042.
[16]周海燕,徐冰,史新元,等.统计过程控制在栀子前处理生产工艺中的应用[J].中国实验方剂学杂志,2012,18(11):16-20.
[17]Jiang M M,Wang Y F,Xu L,et al.Quantitative profiling of polar metabllites in herbal medicine injections for multivariate statistical evaluation based on independence pricipal component analysis[J].PLo S One,2014,9(8):1-8.
[18]Treasurea R J,Krugerb U,Coopera J E,et al.Dynamic multivariate statistical process control using subspace identification[J].J Process Control,2004,14(3):279-292.
[19]徐冰,罗赣,林兆洲,等.基于过程分析技术和设计空间的金银花醇沉加醇过程终点检测[J].高等学校化学学报,2013,34(10):2284-2289.