基于近红外光谱分析技术的丹参多酚酸大孔吸附树脂柱色谱过程监测方法

该文将近红外光谱作为过程分析技术的工具,研究并建立了丹参多酚酸大孔吸附树脂柱色谱过程监测方法。采用7个正常操作批次建立柱色谱过程的多变量统计过程控制(MSPC)模型,以2个测试批次(包括1个正常操作批次和1个异常操作批次)验证模型的监测性能。结果显示,MSPC模型对柱色谱过程具有良好的监测能力。同时,采用偏最小二乘(PLS)建立了柱色谱过程中迷迭香酸、紫草酸和丹酚酸B 3个关键质量指标的近红外光谱定量校正模型,验证结果显示模型具有满意的预测性能。将以上2种模型相结合应用,能够有效地实现对丹参多酚酸大孔吸附树脂柱色谱过程的实时监测,并对关键质量指标进行在线分析。该研究所建立的过程监测方法可以为中药制药过程分析技术的开发提供参考。

Monitoring method for macroporous resin column chromatography process of salvianolic acids based on near infrared spectroscopy

To study and establish a monitoring method for macroporous resin column chromatography process of salvianolic acids by using near infrared spectroscopy (NIR) as a process analytical technology (PAT).The multivariate statistical process control (MSPC) model was developed based on 7 normal operation batches, and 2 test batches (including one normal operation batch and one abnormal operation batch) were used to verify the monitoring performance of this model. The results showed that MSPC model had a good monitoring ability for the column chromatography process. Meanwhile, NIR quantitative calibration model was established for three key quality indexes (rosmarinic acid, lithospermic acid and salvianolic acid B) by using partial least squares (PLS) algorithm. The verification results demonstrated that this model had satisfactory prediction performance. The combined application of the above two models could effectively achieve real-time monitoring for macroporous resin column chromatography process of salvianolic acids, and can be used to conduct on-line analysis of key quality indexes. This established process monitoring method could provide reference for the development of process analytical technology for traditional Chinese medicines manufacturing.