Multi critical quality attributes monitoring of Chinese oral liquid extraction process with a spectral sensor fusion strategy

Jin Zhang; Xiuhua Xu; Lian Li; Haoyuan Li; Lele Gao; Xiaomei Yuan; Haochen Du; Yongxia Guan; Hengchang Zang

doi:10.1016/j.saa.2022.121317

Multi critical quality attributes monitoring of Chinese oral liquid extraction process with a spectral sensor fusion strategy

Spectrochim Acta A Mol Biomol Spectrosc. 2022 Oct 5:278:121317. doi: 10.1016/j.saa.2022.121317. Epub 2022 May 2.

Authors

Jin Zhang¹, Xiuhua Xu¹, Lian Li¹, Haoyuan Li¹, Lele Gao¹, Xiaomei Yuan², Haochen Du², Yongxia Guan², Hengchang Zang³

Affiliations

¹ National Medical Products Administration Key Laboratory for Technology Research and Evaluation of Drug Products, School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, Jinan 250012, China.
² State Key Laboratory of Generic Manufacture Technology of Chinese Traditional Medicine, Lunan Pharmaceutical Group Co. Ltd., Linyi 276006, China.
³ National Medical Products Administration Key Laboratory for Technology Research and Evaluation of Drug Products, School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, Jinan 250012, China. Electronic address: zanghcw@126.com.

PMID: 35537260
DOI: 10.1016/j.saa.2022.121317

Abstract

The traditional Chinese medicine (TCM) extraction process is a complicated dynamic system with many variables and disturbance. Therefore, multi critical quality attributes (CQAs) monitoring is of great significance to understand the whole process. Spectroscopy is a powerful process analytical tool used for process understanding. However, single senor sometimes could not provide comprehensive information. Sensor fusion is a very practical method to overcome this deficiency. In this study, the extraction process of Xiao'er Xiaoji Zhike Oral Liquid (XXZOL) was carried out in pilot scale, where near infrared (NIR) spectroscopy and mid infrared (MIR) spectroscopy were collected to determine the concentrations of seven CQAs (synephrine, arecoline, chlorogenic acid, forsythoside A, naringin, hesperidin and neohesperidin) during extraction process. Based on fused data blocks, fusion partial least squares (PLS) models were established. Two fusion data blocks are obtained from the concatenation of original spectra (low-level data fusion) and the concatenation of characteristic variables based on band selection (mid-level data fusion) respectively. The results indicated that for all seven analytes, the mid-level data fusion models were superior to the single spectral models, with the prediction performance significantly improved. Specifically, the coefficients of determination (R_p² and R_t²) of NIR, MIR and fusion quantitative models were all higher than 0.95. The relative standard errors of prediction (RSEP) values were all within 10%, except for models of neohesperidin, which were 10.76%, 12.39%, 12.05%, 10.03% for NIR, MIR, low-level and mid-level models respectively. These results demonstrate that it is feasible to monitor the extraction process of Xiao'er Xiaoji Zhike Oral Liquid more accurately and rapidly by fusing NIR and MIR spectroscopy, and the proposed approach also has vital and valuable reference value for the rapid monitoring of the mixed decoction process of other TCM.

Keywords: Data fusion; Extraction process; Mid infrared spectroscopy; Near infrared spectroscopy; Traditional Chinese medicine (TCM); Xiao’er Xiaoji Zhike Oral Liquid.

MeSH terms

China
Chlorogenic Acid
Drugs, Chinese Herbal* / chemistry
Least-Squares Analysis
Medicine, Chinese Traditional
Spectroscopy, Near-Infrared* / methods

Substances

Drugs, Chinese Herbal
Chlorogenic Acid