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.

中文翻译：

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黄柏柱层析过程实时监测第二部分：基于近红外光谱的多元统计过程控制

在天然药物的生产过程中，柱层析分离是关键步骤。但是，目前一般无法监测洗脱过程的真实运行状态。为了解决这个问题，应该开发一种更全面的方法。本研究采用近红外光谱结合多元统计过程控制（MSPC）作为一种免校准方法，实时监测黄柏柱层析过程。三种不同的统计量，包括主成分得分，Hotelling T ²和与模型 X 的距离，用于建立 MSPC 模型。统计数据的可接受范围来自六个正常操作条件 (NOC) 批次，用于监测另外四个 NOC 批次和七个在异常操作条件 (AOC) 下处理的批次的洗脱过程。我们发现后11个批次的运行状态都可以准确无误地检测出来。基于MSPC的免校准监测方法有望成为一种有效的工具，可用于柱色谱过程的实时监测和故障分析。