近红外光谱技术用于血必净注射液提取过程的在线检测研究  

Near-infrared spectroscopy on-line and real-time monitoring of extraction process of Xuebijing Injection

作　　者：金叶[1] 丁海樱[1] 吴永江[1] 刘雪松[1] 陈勇[1] 

机构地区：[1]浙江大学药学院,杭州310058

出　　处：《药物分析杂志》2012年第7期1214-1221,1234,共9页Chinese Journal of Pharmaceutical Analysis

基　　金：浙江省重大科技计划(2008C03005);国家"十一五"科技支撑计划(2006BAI06A08)资助

摘　　要：目的:采用近红外透射光谱法,建立血必净注射液提取过程各质控指标的快速定量分析模型,并进行提取终点的快速判断,实现提取过程的在线检测。方法:以川芎、丹参和当归3种药材混合提取过程为例,采用偏最小二乘法回归(PLSR)分别建立阿魏酸浓度和含固量的定量校正模型,并将模型应用于提取过程的在线检测。使用移动块标准偏差(MBSD)算法实现对提取终点的快速判断。此外,采用模型更新方法,扩充原有模型,提高模型的稳定性和预测精度。结果:所建立的阿魏酸和含固量校正模型相关系数均达到0.986,采用所建模型进行在线分析,预测结果与实际测定值相关系数均大于0.967,预测相对偏差(RSEP)小于10%,相对分析误差(RPD)大于3。同时,MBSD算法的终点判断结果与实际相符。此外,将新的样品加入原校正模型进行模型更新后预测效果有所改善。结论:研究结果表明,利用近红外光谱技术可以实现提取过程中阿魏酸浓度和含固量的快速检测,并可快速判断提取终点。另外,模型更新方法有利于解决因药材质量、工况等发生变化导致的"模型失效"问题,从而扩展模型的使用范围。Objective ：To establish a rapid quantitative analysis model for quality control of Xuebijing Injection ex- traction with application of near - infrared （NIR） spectroscopy, and quickly determine the end point of extraction process, so as to realize on - line monitoring of the extraction process of Xuebijing Injection. Methods： Taking mixed extraction process of Ligusticum chuanxiong Hort. , Salvia miltiorrhiza Bge. and Angelica sinensis （ Oliv. ） Diels for an example, partial least squares regression （PLSR） models were developed for the parameters of interest ： total solid content and ferulic acid. The established PLS calibration models were used for on - line and real - time monitoring of the extraction process, and the moving block of standard deviation （MBSD） was used to identify the extraction end point. Furthermore, a model updating method was adopted to improve the stability and prediction ac- curacy of the calibration models. Results： The correlation coefficients of total solid content and ferulic acid models have reached 0. 986. When the established models were applied to on - line monitoring, the correlation coefficients of prediction （r） and the residual predictive deviations （RPD） were above 0. 967 and 3, respectively, and the rel- ative standard errors of predictions （RSEP） were less than 10%. The result of MBSD was generally coincided with the variation of actual -measured ferulic acid concentration. In addition, the predictive accuracy was significantly improved after model updating with new samples. Conclusions： In this study, NIR spectroscopy was successfully applied to predicting total solid content and ferulic acid concentration in real -time and rapid determination of theextraction end point. Moreover, to solve the problem of calibration invalidation, the method of model updating was utilized to extend the use of established models and obtain better prediction results.

关 键 词：近红外光谱 提取工艺 在线检测 提取 血必净注射液 阿魏酸 模型更新 终点判断 

分 类 号：R917[医药卫生—药物分析学]