ABSTRACT
The chemical properties of characteristic components are significant to the manufacturing quality control of big brand traditional Chinese medicine. In this study, the Huangjing Zanyu Capsules were used as the research carrier to determine the content of five characteristic components including icraiin, emodin, schisandrin A, 2,3,5,4'-tetrahydroxystilbene-2-O-β-D-glucoside, and osthole simultaneously by high-performance liquid chromatography(HPLC). The results showed that the chemical properties of five cha-racteristic components had a good linear relationship(r>0.999 9) within the quantitative range; the relative standard deviations(RSD) was 0.11%-2.0% and 0.25%-2.8% respectively for intra-day and inter-day precision; the RSD of repeatability was 1.8%-2.6%; the RSD of stability within 48 hours was 0.19%-2.8%, and the average recovery rate was 95.52%-100.1%, all meeting the requirements of pharmaceutical quantitative analysis. Additionally, the interval estimation method was used to directly reflect the distribution of samples with abnormal chemical properties of characteristic components, and the results showed ten samples were detected beyound the 95% control line of confidence level. Multivariate statistical process control(MSPC) method was used to monitor the abnormal samples of Huangjing Zanyu Capsules collectively, and the results showed that two samples were beyond the 95% control line of Hotelling's T~2 and three samples beyond the 95% control line of squared prediction error(SPE), indicating consistent quality control of Huangjing Zanyu Capsules. In conclusion, the proposed method is not only accurate and efficient but also a compensation for the traditional single-component quality control method, providing a scientific basis for the quality control in manufacturing process of Huangjing Zanyu Capsules. Furthermore, it could also serve as a reference method for the quality control in manufacturing big brand traditional Chinese medicine.
Subject(s)
Capsules , Chromatography, High Pressure Liquid , Drugs, Chinese Herbal , Medicine, Chinese Traditional , Quality ControlABSTRACT
Spatial distribution uniformity is the critical quality attribute(CQA) of Ginkgo Leaves Tablets, a variety of big brand traditional Chinese medicine. The evaluation of the spatial distribution uniformity of active pharmaceutical ingredients(APIs) in Ginkgo Leaves Tablets is important in ensuring their stable and controllable quality. In this study, hyperspectral imaging technology was used to construct the spatial distribution map of API concentration based on three prediction models, further to realize the visualization research on the spatial distribution uniformity of Ginkgo Leaves Tablets. The region of interest(ROI) was selected from each Ginkgo Leaves Tablet, with length and width of 50 pixels, and a total of 2 500 pixels. Each pixel had 288 spectral channels, and the number of content prediction data could reach 1×10~5 for a single sample. The results of the three models showed that the Partial Least Squares(PLS) model had the highest prediction accuracy, with calibration set determination coefficient R_(pre)~2 of 0.987, prediction set determination coefficient R_(pre)~2 of 0.942, root mean square error of calibration(RMSEC) of 0.160%, and root mean square error of prediction(RMSEP) of 0.588%. The classical least-squares(CLS) model had a greater prediction error, with the RMSEP of 0.867%. Multivariate Curve Resolution-Alternating Least Square(MCR-ALS) model showed the worst predictive ability among the three models, and it couldn't realize content prediction. Based on the prediction results of PLS and CLS models, the spatial distribution map of APIs concentration was obtained through three-dimensional data reconstruction. Furthermore, histogram method was used to evaluate the spatial distribution uniformity of API. The data showed that the spatial distribution of APIs in Ginkgo Leaves Tablets was relatively uniform. The study explored the feasibility of visualization of spatial distribution of Ginkgo Leaves Tablets based on three models. The results showed that PLS model had the highest prediction accuracy, and MCR-ALS model had the lowest prediction accuracy. The research results could provide a new strategy for the visualization method of quality control of Ginkgo Leaves Tablets.
Subject(s)
Calibration , Ginkgo biloba , Least-Squares Analysis , Medicine, Chinese Traditional , Plant Leaves , Quality Control , Spectroscopy, Near-Infrared , TabletsABSTRACT
Identification of critical quality attribute(CQA) is crucial in quality control of Tongren Niuhuang Qingxin Pills(TRNHQXP). In this study, 661 active components in TRNHQXP were selected by liquid chromatography-mass spectrometry(LC-MS) and network pharmacology based on reported data and TCMSP, BATMAN-TCM, and TCMID databases, as well as mass spectrometry data, and 1 413 targets of the active components were obtained through SwissTargetPrediction. The 152 potential targets obtained from the intersection of predicted targets with 456 stroke targets underwent functional enrichment analysis by Metascape. The 27 Chinese medicinals in TRNHQXP were divided into four sets according to efficacies. Thirty-seven key targets in the blood-activating and stasis-resolving set and 41 in the tonifying set were screened out. On the basis of these potential key targets, 137 potential key CQA of TRNHQXP for stroke were reversely predicted. This study revealed the possible mechanism of TRNHQXP in treating stroke and established a modular identification method for the potential CQA of big brand traditional Chinese medicine(TCM) based on efficacies and chemical properties. Consequently, the CQA of TRNHQXP were identified by this method, which has provided a reference for the following experimental studies of CQA.