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Licorice, a medicinal herb and food flavor ingredient, has been widely used in traditional Chinese medicine (TCM) for the past 4,000 years. In this study, we propose a new quality evaluation approach for licorice quality control based on the key quality attributes commonly used in TCM. The high quality of TCM formulations is ensured by verifying the genuine origin and implementing good agricultural and collection practices for each medicinal herb. In our study, the genuine production area, the harvest season, and the number of growth years were considered the key quality attributes of TCM. To ensure the representativeness of our analysis, we obtained a total of 158 licorice sample batches that differed in the number of growth years, the location of the production areas, and the season for harvesting. Initially, the 158 sample batches were subjected to ultra-high-performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry (UHPLC-QTOF-MS/MS). A preliminary screen identified 11 licorice compounds related to the three key quality attributes of TCM formulations. Ananalysis by ultra-high-performance liquid chromatography coupled with triple quadrupole tandem mass spectrometry (UHPLC-TQ-MS/MS) verified the presence of 34 compounds in all licorice samples. These 34 compounds included the 11 compounds related to the three key quality attributes of the samples, along with other bioactive components identified in previous studies. After using UHPLC-TQ-MS/MS to assess the signal peak intensities of the 34 compounds, we selected 17 licorice compounds to establish sample content evaluation indices, which were determined by high-performance liquid chromatography at four different wavelengths in all 158 licorice sample batches. Finally, the screen identified nine compounds that were closely associated with the quality attributes of licorice based on principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA). Our results suggested that liquiritin and eight other compounds could be used as quality control indicators of licorice, which provided a foundation to establish the TCM quality composite evaluation index (TCM QCEI). In summary, this research concept can serve as a reference for research on quality markers and the evaluation of TCM formulations.

In this study, the texture analyzer acupuncture pressure sensor was used to objectively characterize thequot;herb soaking with exact amount of waterquot; for moistening process of ginseng. The single factor rotation experiment was used to investigate the effects of puncture speed, puncture depth and puncture site on puncture force and work. According to ginseng processing method in Chinese Pharmacopoeia, ginseng medicinal materials with diameters of about 1 cm and 2 cm were selected, and puncture experiments were carried out at the set measurement time to determine the hardness, work and water absorption of the ginseng moistening process. The endpoint threshold for the ginseng softening process was determined and verified. To reflect the actual internal conditions of the ginseng softening process, the puncture depth was preferably 70%, and the puncture speed was 30 mm·min~(-1). In the ginseng moistening process, the softening hardness and the puncture work were in accordance with the first-order kinetic equation y=a×exp(-k×x). The 0 h initial hardness a of 1 cm and 2 cm ginseng herbs were 289.8 N and 1 227 N, and the rate constants K were 0.149 4 N·h~(-1) and 0.100 7 N·h~(-1), respectively. After the ginseng was completely softened, the force required for puncture was 10 N, which can be used as the standard forquot;drug penetrationquot;. At this time, the water absorption rate of ginseng was 70%-100%. The softening time of ginseng with a diameter of 1 cm was about 20-22 h, and the softening time of ginseng with a diameter of 2 cm was about 40-46 h. A needle-type pressure sensor was used to accurately determine the end point of the softening process of ginseng and reduce the loss of active ingredients. The study results provide reference for the softening process kinetics and the process intelligent monitoring of other dried roots and rhizomes.

In this paper, the inline turbidity sensor technology was used to quantify the turbidity of the solution during the dissolution of Chinese medicine granules. The probe measurement position and the magnetic stirring speed were optimized. As a result, the stirring speed was 400 r·min~(-1), and the probe position was at 1/4 of the diameter of the beaker. The measurement results were accurate and reliable. Totally 105 batches of commercially available Chinese medicine granules were collected and dissolved according to the requirements of the Chinese Pharmacopoeia. At the time point of 5 min, 57 batches of granules were completely dissolved, and the corresponding turbidity values ranged between 0-70 FTU; 32 batches of granules showed a slight turbidity, and the corresponding turbidity values ranged between 70-350 FTU; 14 batches of granule solution were turbid, and the corresponding turbidity values ranged between 350-2 000 FTU; two batches of granule solution were heavily turbid, and the corresponding turbidity values weregt;2 000 FTU. Among the above results, the number of batches in line with the pharmacopoeia dissolution requirement was 84.76%, and the dissolution of some granules still needed to be improved. The turbidity sensor recorded the change curve of turbidity value over time(solubility behavior curve). The degree of important of disintegration and dissolution during the dissolution process showed disintegrationgt; dissolution, disintegration≈dissolution, disintegrationlt; dissolution. The dissolution behavior of the granules can be classified into three categories. The analysis of the mechanism in the process of granule solubility provides a basis for product process improvement.

Along with the striding of the Chinese medicine(CM) manufacturing toward the Industry 4.0, some digital factories have accumulated lightweight industrial big data, which become part of the enterprise assets. These digital assets possess the possibility of solving the problems within the CM production system, like the Sigma gap and the poverty of manufacturing knowledge. From the holistic perspective, a three-tiered architecture of CM industrial big data is put forward, and it consists of the data integration layer, the data analysis layer and the application scenarios layer. In data integration layer, sensing of CM critical quality attributes is the key technology for big data collection. In data analysis and mining layer, the self-developed iTCM algorithm library and model library are introduced to facilitate the implementation of the model lifecycle methodologies, including process model development, model validation, model configuration and model maintenance. The CM quality transfer structure is closely related with the connection mode of multiple production units. The system modeling technologies, such as the partition-integration modeling method, the expanding modeling method and path modeling method, are key to mapping the structure of real manufacturing system. It is pointed out that advance modeling approaches that combine the first-principles driven and data driven technologies are promising in the future. At last, real-world applications of CM industrial big data in manufacturing of injections, oral solid dosages, and formula particles are presented. It is shown that the industrial big data can help process diagnosis, quality forming mechanism interpretations, real time release testing method development and intelligent product formulation design. As renewable resources, the CM industrial big data enable the manufacturing knowledge accumulation and product quality improvement, laying the foundation of intelligent manufacturing.

The project was launched to analyze the effects of sulfur-fumigated Ophiopogonis Radix on endogenous metabolites in rats by metabonomics. The preparation method of sulfur-fumigated Ophiopogonis Radix in laboratory was established. Then the blood samples of SD rats in blank group,Ophiopogonis Radix extract group and sulfur-fumigated Ophiopogonis Radix extract group were investigated by UHPLC-Q-Exactive. The differential metabolites were screened and identified by PCA(principal component analysis),OPLSDA(orthogonal partial least squares discriminant analysis) and variable importance projection(VIP),and the metabolic pathways were analyzed. Finally,a total of 15 potential biomarkers were identified. Compared with the samples of Ophiopogonis Radix extract group,sulfur-fumigated Ophiopogonis Radix mainly affected the biosynthesis and metabolism of amino acids in normal rats. Its mechanism may be related to the biosynthesis of phenylalanine,tyrosine,tryptophan and aminoacyl-tRNA as well as the metabolism of phenylalanine and tryptophan. Based on UHPLC-HRMS metabonomics,this paper discussed the effects of sulfur-fumigated Ophiopogonis Radix on endogenous metabolites in rats,which provided an idea for the metabolic study of other sulfur-fumigated traditional Chinese medicines.

This study is aimed to propose a continual improvement strategy based on quality by design (QbD). An ultra high performance liquid chromatography (UPLC) method was developed to accomplish the method transformation from HPLC to UPLC of Panax notogineng saponins (PNS) and achieve the continual improvement of PNS based on QbD, for example. Plackett-Burman screening design and Box-Behnken optimization design were employed to further understand the relationship between the critical method parameters (CMPs) and critical method attributes (CMAs). And then the Bayesian design space was built. The separation degree of the critical peaks (ginsenoside Rg₁ and ginsenoside Re) was over 2.0 and the analysis time was less than 17 min by a method chosen from the design space with 20% of the initial concentration of the acetonitrile, 10 min of the isocratic time and 6%•min⁻¹ of the gradient slope. At last, the optimum method was validated by accuracy profile. Based on the same analytical target profile (ATP), the comparison of HPLC and UPLC including chromatograph method, CMA identification, CMP-CMA model and system suitability test (SST) indicated that the UPLC method could shorten the analysis time, improve the critical separation and satisfy the requirement of the SST. In all, HPLC method could be replaced by UPLC for the quantity analysis of PNS.

In this paper, under the guidance of quality by design (QbD) concept, the control strategy of the high shear wet granulation process of the ginkgo leaf tablet based on the design space was established to improve the process controllability and product quality consistency. The median granule size (D50) and bulk density (Da) of granules were identified as critical quality attributes (CQAs) and potential critical process parameters (pCPPs) were determined by the failure modes and effect analysis (FMEA). The Plackeet-Burmann experimental design was used to screen pCPPs and the results demonstrated that the binder amount, the wet massing time and the wet mixing impeller speed were critical process parameters (CPPs). The design space of the high shear wet granulation process was developed within pCPPs range based on the Box-Behnken design and quadratic polynomial regression models. ANOVA analysis showed that the P-values of model were less than 0.05 and the values of lack of fit test were more than 0.1, indicating that the relationship between CQAs and CPPs could be well described by the mathematical models. D₅₀ could be controlled within 170 to 500 μm, and the bulk density could be controlled within 0.30 to 0.44 g•cm⁻³ by using any CPPs combination within the scope of design space. Besides, granules produced by process parameters within the design space region could also meet the requirement of tensile strength of the ginkgo leaf tablet..