ABSTRACT
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.
Subject(s)
Capsules , Drugs, Chinese Herbal , Medicine, Chinese Traditional , Powders , Quality ControlABSTRACT
The physical properties of ginkgo leaves extract(GLE) are the critical quality attributes for the control of the manufacturing process of ginkgo leaves preparations. In this study, 53 batches of GLE with different sources from the real world were used as the objects to carry out the research from 3 levels. First, based on micromeritics evaluation method, a total of 29 physical attribute quality parameters in five dimensions were comprehensively characterized, with a total of 1 537 data points. Further, with use of physical fingerprinting technology combined with similarity evaluation, the powder physical properties of 53 batches of GLE showed obvious differences from an overall perspective, and the similarity of the physical fingerprints was 0.876 to 1.000. Secondly, hierarchical clustering analysis(HCA) and principal component analysis(PCA) models were constructed to realize the reliable identification and differentiation of real-world materials produced by GLE from different sources. Multivariate statistical process control(MSPC) model was used to create GLE material Hotelling T~2 and squared prediction error(SPE) control charts. It was found that the SPE score of B_(21) powder exceeded the 99% confidence control limit by 22.495 9, and the SPE scores of A_1 and C_(10) powder exceeded the 95% confidence control limit by 16.099 2, realizing the determination of abnormal samples in the materials of GLE from the production in real world. Finally, the physical quality control method of GLE in the production process of ginkgo leaves preparations was established in this study, providing a reference for the quality control methods of ginkgo leaves preparations in their manufacturing process.
Subject(s)
Drugs, Chinese Herbal , Ginkgo biloba , Medicine, Chinese Traditional , Plant Extracts , Plant Leaves , Powders , 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.