The Key Laboratory of TCM Information Engineering of State Administration of Traditional Chinese Medicine

Beijing, China

The Key Laboratory of TCM Information Engineering of State Administration of Traditional Chinese Medicine

Beijing, China
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Xue Z.,Beijing University of Chinese Medicine | Xue Z.,The Key Laboratory of TCM Information Engineering of State Administration of Traditional Chinese Medicine | Xu B.,Beijing University of Chinese Medicine | Xu B.,The Key Laboratory of TCM Information Engineering of State Administration of Traditional Chinese Medicine | And 10 more authors.
Spectrochimica Acta - Part A: Molecular and Biomolecular Spectroscopy | Year: 2017

This study presented a new strategy of overall uncertainty measurement for near infrared (NIR) quantitative analysis of cryptotanshinone in tanshinone extract powders. The overall uncertainty of NIR analysis from validation data of precision, trueness and robustness study was fully investigated and discussed. Quality by design (QbD) elements, such as risk assessment and design of experiment (DOE) were utilized to organize the validation data. An “I × J × K” (series I, the number of repetitions J and level of concentrations K) full factorial design was used to calculate uncertainty from the precision and trueness data. And a 27–4 Plackett–Burmann matrix with four different influence factors resulted from the failure mode and effect analysis (FMEA) analysis was adapted for the robustness study. The overall uncertainty profile was introduced as a graphical decision making tool to evaluate the validity of NIR method over the predefined concentration range. In comparison with the T. Saffaj's method (Analyst, 2013, 138, 4677.) for overall uncertainty assessment, the proposed approach gave almost the same results, demonstrating that the proposed method was reasonable and valid. Moreover, the proposed method can help identify critical factors that influence the NIR prediction performance, which could be used for further optimization of the NIR analytical procedures in routine use. © 2016 Elsevier B.V.


Xu B.,Beijing University of Chinese Medicine | Xu B.,The Key Laboratory of TCM Information Engineering of State Administration of Traditional Chinese Medicine | Wu Z.,Beijing University of Chinese Medicine | Wu Z.,The Key Laboratory of TCM Information Engineering of State Administration of Traditional Chinese Medicine | And 8 more authors.
Analytica Chimica Acta | Year: 2012

Ethanol precipitation plays a major role in the pretreatment of Flos Lonicerae Japonicae of Qingkailing injection, and is also one of the most popular purification techniques in Chinese herbal medicines. In order to monitor and have a better understanding of the ethanol precipitation process, a PLS model was built based on NIR spectroscopy and HPLC analysis of chlorogenic acid content within the framework of FDA's PAT initiative. Nevertheless, due to the complex mechanism of and the raw materials' natural variability introduced into the ethanol precipitation process, it was unable to foresee the variations in new batches which may jeopardize the robustness of the established model. Therefore, based on the simple interval calculation (SIC) theory, a new model expansion updating strategy which could continuously expand the variation coverage of the calibration model along with the batch proceeding of ethanol precipitation process was proposed. Effects of model updating were validated by an individual batch with 60 samples. After two times of updating, the root mean squared error of prediction (RMSEP) decreased from 0.268mgmL -1 to 0.199mgmL -1, while the insiders in the object status plot (OSP) increased from 44 to 58, demonstrating the good performance of the proposed approach. © 2012 Elsevier B.V.


Wu Z.,Beijing University of Chinese Medicine | Wu Z.,The Key Laboratory of TCM Information Engineering of State Administration of Traditional Chinese Medicine | Xu B.,Beijing University of Chinese Medicine | Xu B.,The Key Laboratory of TCM Information Engineering of State Administration of Traditional Chinese Medicine | And 8 more authors.
Journal of Pharmaceutical and Biomedical Analysis | Year: 2012

The feasibility of near-infrared spectroscopy (NIRS) for chlorogenic acid content analysis in ethanol precipitation process of water extract of Lonicera japonica was verified in this work. A calibration and validation set was designed for the conception and evaluation of the method adequacy. An experimental protocol was then followed, involving two different NIR instruments for data acquisition. On the basis of this protocol, the model was developed based on partial least squares regression (PLS) and the determination coefficient (R2 cal and R2 val), standard error of calibration and prediction (SEC and SEP) were 0.9962, 0.9955, 111.1μg/mL and 107.1μg/mL for Holographic Grating NIR instrument, and 0.9984, 0.9971, 53.6μg/mL and 83.3μg/mL for Fourier Transform NIR instrument. However, such above criteria did not clearly demonstrate the model's prediction error over each analyzed content range. Consequently, a novel approach based on accuracy profile which allowed the acquisition of the lower limit of quantification (LLOQ) was used to validate the robustness and accuracy of PLS model. The resulting accuracy profile showed that PLS model was able to determine chlorogenic acid content by two NIR systems, whose LLOQ was about 1550μg/mL. It was concluded that the two NIR systems were suitable for use as Process Analytical Technology (PAT) to understand ethanol precipitation process of water extract of Lonicera japonica. © 2011 Elsevier B.V.

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