(695d) Monitoring Batch-to-Batch Reproducibility of TCM Production Process Using in-Line NIR Spectroscopy Combined With MSPC Method

Monitoring batch-to-batch reproducibility of TCM production process using in-line NIR spectroscopy combined with MSPC method

Wenlong Li, Haifan Han, Haibin Qu *

(Pharmaceutical Informatics Institute, Zhejiang University, Hangzhou 310058, China)

Traditional Chinese medicine (TCM) products are usually manufactured through batch processes. To improve the 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 statistical process control (MSPC) method as an efficient process analytical technology (PAT) tool, is presented in this study for the real-time batch process monitoring. Two representative technical processes, the alkaline precipitation of the compound E Jiao oral liquid and the liquid preparation process of Tanreqing injection, were taken as examples. The process NIR spectral data ( three-way matrix) was unfolded in “variable-wise” way into the two-dimensional matrix, and multi-way principal component analysis (MPCA) model were developed based on the rearranged data of the normal operation condition (NOC) batches. Three kinds of multivariate control charts (scores, Hotelling T²and DModX) were used to monitor the evolution of test batches with artificial batch variations, including the change of starting material quality attributes and abnormal operation conditions.

Case 1: Alkaline precipitation is a critical unit operation used in the manufacture of compound E-Jiao oral liquid, which has the recognized curative effect of invigorating vital energy and nourishing blood. The in-line NIR spectra of 29 batches of feed liquid, including 13 NOC batches and 16 AOC (abnormal operation conditions, AOC) batches, were collected using an Antaris II Fourier transformation (FT) NIR spectrometer (Thermo Electron Co., Madison, USA) with a handheld fiber-optics probe over the wave number range of 4000- 10,000 cm^-1 at 4 cm^-1 data interval. The MSPC models were developed using the SIMCA 13 software (Umetrics, MKS Instruments Inc., Sweden), and the effectiveness of the proposed approach was evaluated through experimental verifications. 10 batches run under normal operating conditions were used to study the batch-to-batch variation and to definite the MSPC control limits. Another 3 NOC batches and 16 AOC batches, which were operated with abnormal densities of the raw materials, or under abnormal pH values, solid-to-liquid ratios, and heating-up temperatures, were used as the test batches to challenge the established models. As illustrated with test batches, the established monitoring model can identify NOC or AOC batches accurately, and detect kinds of deviations from NOC batches using the control charts. The consistent monitoring result was derived according to the score and Hotelling T²control charts, and the two types of control charts could be individually or collectively used for monitoring batch evolution.

Case 2: The liquid preparation process of bear bile powder extract is a critical operating unit during the manufacture of Tanreqing injection, which is used chiefly in treating infection of the upper respiratory tract and serious influenza. The simulation experiments were designed, including 8 NOC batches and 7 AOC batches (with abnormal solid-to-liquid ratios, sodium hydroxide dosage, heating-up temperature, or stir speeds). Spectra were in-line collected from a simulation device using an Antaris MX Fourier FT-NIR spectrometer (Thermo Electron Co., Madison, USA). The MSPC model for the in-line monitoring of liquid preparation process of bear bile powder extract was developed after the selection of 6 NOC batches as calibration set. The fault monitoring was performed through the sore charts, Hotelling T²charts and DModX charts, with the average values of the calibration batches as “golden batch trajectory” and ±3 standard deviations as control ranges. The trajectories of the test NOC batches were all lie in the control range, and the trajectories of the test AOC batches were all out of the controlled range in various ways. The results suggested that the established method can be used for the in-line monitoring and control of the fluid preparation process of bear bile powder extract effectively.

The batch process monitoring approach presented in this study, using in-line NIR spectroscopy combined with multivariate data analysis, was found very effective for the 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, which can enhance process understanding and open up the possibility of process control to achieve the desired product quality in the manufacture of TCM. The key to establish a satisfactory MSPC model is to select good batches representative of normal operating conditions for model training and to establish appropriate control limits. To further diagnose the causes of process abnormalities, contribution plots could be used in combination with the control charts to identify NIR wavelengths associated with a process fault/raw material change, and additional models are also needed to be established between the process parameters and NIR spectral data.