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

End-point Detection of the Alcohol Adding Process in Alcohol Precipitation of Lonicerae Japonicae Based on Design Space and Process Analytical Technology

建立了一种新的基于过程分析技术(PAT)和质量源于设计(QbD)设计空间的中药制药过程终点分析与控制方法.以近红外(NIR)光谱技术为PAT工具,采集正常操作条件下制药过程的多批次NIR光谱;采用主成分分析结合移动块相对标准偏差(PCA-MBRSD)法,确定每一批次过程的理想终点样本(DEPs),由多批DEPs的光谱信息构成过程终点设计空间;在过程终点设计空间确定的范围内,建立多变量统计过程控制(MSPC)模型,利用多变量Hotelling T2和SPE控制图对过程终点进行判断.应用上述方法,进行了金银花醇沉加醇过程终点检测研究,结果表明该方法灵敏、准确,适宜于中药制药过程终点检测.

Under the guidance of the FDA＇ s process analytical technology （PAT） initiative and the ICH＇ s quality by design（QbD） principles, a new approach was applied for the end-point detection of the pharmaceu tical process of Chinese medicine preparations. Generally, three steps were included in the proposed ap proach： （1） perform the NIR analysis for the batch process under normal operating conditions （NOCs）, and collect the NIR spectra of different batches; （2） determine the desired end-points （DEPs） for every NOCs batch using the PCA based moving window relative standard deviation （PCA-MBRSD） method. Then, the QbD design space was defined, depending on these DEPs; （3） within the area specified by the design space, the multivariate statistical process control（MSPC） strategy was introduced, and the Hotelling 1,2 and SPE con trol chart were established to monitor and detect the end-point of the manufacturing process. The above meth- ods were tested on the end-point detection of the alcohol adding process of alcohol precipitation of Lonicerae Japorticae water extract. The results demonstrated that the sensitivity and accuracy of the proposed approach were satisfactory.