Real-time monitoring of the column chromatographic process of Phellodendri Chinensis Cortex part II: multivariate statistical process control based on near-infrared spectroscopy

Abstract

In the manufacturing process of natural medicines, column chromatographic separation is a critical step. However, the real operating status of the elution process generally cannot be monitored currently. To address this issue, a more comprehensive method should be developed. In this study, near-infrared spectroscopy combined with multivariate statistical process control (MSPC) was used as a calibration-free method for the real-time monitoring of the column chromatographic process of Phellodendri Chinensis Cortex. Three different statistics, comprising the principal component score, Hotelling T² and distance to model X, were applied to establish an MSPC model. The acceptable ranges of the statistics were obtained from six normal operating condition (NOC) batches, which were used to monitor the elution processes of another four NOC batches and seven batches processed under abnormal operating conditions (AOC). We found that the operating status of all the latter eleven batches could be accurately detected with no misjudgment. The calibration-free monitoring method based on MSPC is expected to be an efficient tool that can be applied for the real-time monitoring and fault analysis of the column chromatographic process.