Research on dynamic on-line monitoring method of moisture attribute in three honey-processed Chinese herbal slice based on in-situ general model / 药学学报

Aiming at the hysteresis and destructiveness of off-line static detection of critical quality attribute of the moisture content of the raw material unit of the traditional Chinese medicine manufacturing process, honey-processed Tussilago farfara, honey-processed Astragalus and honey-processed Glycyrrhiza uralensis were used as the research carriers, and the drying method was used to measure the moisture content as a reference value. The moving stage was used to simulate the movement process of samples on the conveyor belt in the actual on-site production process, and near-infrared (NIR) spectra were collected, combined with machine learning, to establish NIR on-site dynamic detection model of moisture content in multi-variety honey-processed Chinese herbal slice. The results show that the second derivative method is used to preprocess the spectrum. The number of decision trees (ntree), the number of random features (max feature), and the minimum number of samples for generating leaf nodes (node size) are selected: 46, 76, and 8, respectively. The quantitative analysis model of moisture content has the best effect. The prediction coefficient of determination (the prediction coefficient of determination, R2pre) and the root mean square error of prediction (root mean square error of prediction, RMSEP) of the model were 0.903 2 and 0.330 2, respectively. The NIR quantitative model for the moisture content of multi-variety honey-processed Chinese herbal slice established in this study has good predictive performance, and can achieve rapid, accurate and non-destructive quantitative analysis of the moisture content of honey-processed Tussilago farfara, honey-processed Astragalus and honey-processed Glycyrrhiza uralensis at the same time, and provides a method for determining the moisture content of honey-processed Chinese herbal slice of the raw material unit of the traditional Chinese medicine manufacturing process.

Criticalquality attribute assessment of big brand traditional Chinese medicine: visualization method for quality control of Ginkgo Leaves Tablets based on spatial distribution uniformity / 中国中药杂志

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.

Critical quality attribute assessment of big brand traditional Chinese medicine: process quality control method of Suhuang Zhike Capsules intermediate based on physical properties of powder and granules / 中国中药杂志

The physical properties of powder and granules are the critical quality attributes for the process control of Suhuang Zhike Capsules, a big brand traditional Chinese medicine. This paper took the production of 25 batches of real-world Suhuang Zhike Capsules dry extract powder and granules intermediates as the research object. Firstly, a method for testing the physical properties of Suhuang Zhike Capsules powder and granules with 19 physical indicators was established. The results showed that the granules of dry extract powder after granulation had a smaller particle size, wider particle size distribution range and poor fluidity, which easily caused the problem of over-limit capsule loading. Secondly, correlation analysis, principal component analysis and cluster analysis were used for mathematical statistics. The correlation analysis showed that the density of dry extract powder could affect the chroma and fluidity. At the same time, the particle size in the granules had a stronger effect on the chroma and fluidity than the density. The study also found that the particle size and hygroscopicity of dry extract powder were potentially key physical properties that affected the physical properties of granules. Furthermore, the results of principal component analysis and cluster analysis showed that the consistency of the physical properties between the dry extract powder and intermediate granules was relatively poor. To this end, similarity analysis was carried out, and the quality control method of powder and granules based on physical fingerprint was established. The results showed that the physical fingerprint similarity of 25 batches of dry extract powder was 0.639-0.976, and the physical fingerprint similarity of the gra-nules was 0.716-0.983. With the similarity of 0.85 as the threshold, the batches with abnormal physical properties could be identified. In this study, the process quality control method of Suhuang Zhike Capsules based on the physical properties of powder and granules was established finally, which realized the identification of abnormal batches, and provided a reference for the process quality control of Suhuang Zhike Capsules.