Monitoring batch-to-batch reproducibility of liquid-liquid extraction process using in-line near-infrared spectroscopy combined with multivariate analysis

Traditional Chinese medicine (TCM) products are usually manufactured through batch processes. To improve batch-to-batch reproducibility, the feasible approaches for real-time monitoring of batch evolution need to be developed. In-line near-infrared (NIR) spectroscopy combined with multivariate data analysis as an efficient process analytical technology (PAT) tool, is presented in this study for real-time batch process monitoring. Liquid-liquid extraction is a widely used purification technology in the TCM manufacture, and selected as the example to demonstrate the effectiveness of this PAT tool. Multi-way partial least squares (MPLS) model was developed based on in-line measured NIR spectral data of ten normal operation condition (NOC) batches. Three kinds of multivariate control charts (scores, Hotelling T2 and DModX) were used to monitor the evolution of six test batches with artificial batch variations, including the change of starting material quality attributes and abnormal operation conditions. The approach was found very effective for real-time monitoring of process deviations from NOC batches. It is an alternative promising tool for monitoring batch reproducibility of the unit operations during the manufacture of TCM.