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ObjectiveTo analyze the quantity-quality transfer of standard decoction of Ginseng Radix et Rhizoma（GRR） decoction pieces produced by fresh and traditional cutting， and to provide reference for quality control and application development of the decoction pieces produced by fresh cutting. MethodTen batches of representative GRR decoction pieces produced by fresh and traditional cutting and their standard decoctions were prepared by standard process， and high performance liquid chromatography（HPLC） fingerprint of the standard decoction was established and performed on an Agilent EC-C18 column（4.6 mm×150 mm， 2.7 μm） with acetonitrile（A）-0.1% phosphoric acid aqueous solution（B） as the mobile phase for gradient elution（0-23 min， 18%-21%A； 23-35 min， 21%-28%A； 35-80 min， 28%-32%A）， and the detection wavelength was 203 nm. Then similarity evaluation， principal component analysis（PCA） and partial least squares-discriminant analysis（PLS-DA） of fingerprint of the standard decoction were performed to screen the differential components with variable importance in the projection（VIP） value>1. Quantitative analysis was carried out on the screened known differential components， and combined with the indicators of the dry extract rate and the transfer rate， to explore the differences in the quantity-quality transfer between the standard decoction of GRR decoction pieces produced by fresh and traditional cutting. ResultThe fingerprint similarity of the standard decoction of GRR decoction pieces produced by fresh and traditional cutting was more than 0.950， and 18 common peaks were identified， including 9 identified common peaks. The results of PCA and PLS-DA showed that there were some differences in the contents of index components between the two standard decoctions. The contents of ginsenoside Rg1， Re and Ro in GRR decoction pieces produced by fresh cutting were higher than those in traditional decoction pieces， while the contents of ginsenoside Rb1， Rc ， Rb2 and Rd were lower than those in traditional decoction pieces. The contents of ginsenoside Rg1， Re， Rb1 and Ro in the standard decoction of GRR decoction pieces produced by fresh cutting were higher than those in the standard decoction of traditional decoction pieces， while the contents of ginsenoside Rc ， Rb2 and Rd were comparable between the two standard decoctions. Compared with the standard decoction of the traditional decoction pieces， the average transfer rates of ginsenoside Rg1， Rb1， Rc， Rb2 and dry extract rate of the standard decoction of GRR decoction pieces produced by fresh cutting were significantly increased（P<0.05）， and the average transfer rate of ginsenoside Re and Rd also increased， but the difference was not statistically significant. ConclusionThe dry extract rate， content and transfer rate of index components of standard decoction of GRR decoction pieces produced by fresh cutting are better than those of the standard decoction of traditional decoction pieces， which can provides data support for the subsequent clinical application of fresh cutting products.
ABSTRACT
ObjectiveTo analyze the quantity-quality transfer of standard decoction of Ginseng Radix et Rhizoma（GRR） decoction pieces produced by fresh and traditional cutting， and to provide reference for quality control and application development of the decoction pieces produced by fresh cutting. MethodTen batches of representative GRR decoction pieces produced by fresh and traditional cutting and their standard decoctions were prepared by standard process， and high performance liquid chromatography（HPLC） fingerprint of the standard decoction was established and performed on an Agilent EC-C18 column（4.6 mm×150 mm， 2.7 μm） with acetonitrile（A）-0.1% phosphoric acid aqueous solution（B） as the mobile phase for gradient elution（0-23 min， 18%-21%A； 23-35 min， 21%-28%A； 35-80 min， 28%-32%A）， and the detection wavelength was 203 nm. Then similarity evaluation， principal component analysis（PCA） and partial least squares-discriminant analysis（PLS-DA） of fingerprint of the standard decoction were performed to screen the differential components with variable importance in the projection（VIP） value>1. Quantitative analysis was carried out on the screened known differential components， and combined with the indicators of the dry extract rate and the transfer rate， to explore the differences in the quantity-quality transfer between the standard decoction of GRR decoction pieces produced by fresh and traditional cutting. ResultThe fingerprint similarity of the standard decoction of GRR decoction pieces produced by fresh and traditional cutting was more than 0.950， and 18 common peaks were identified， including 9 identified common peaks. The results of PCA and PLS-DA showed that there were some differences in the contents of index components between the two standard decoctions. The contents of ginsenoside Rg1， Re and Ro in GRR decoction pieces produced by fresh cutting were higher than those in traditional decoction pieces， while the contents of ginsenoside Rb1， Rc ， Rb2 and Rd were lower than those in traditional decoction pieces. The contents of ginsenoside Rg1， Re， Rb1 and Ro in the standard decoction of GRR decoction pieces produced by fresh cutting were higher than those in the standard decoction of traditional decoction pieces， while the contents of ginsenoside Rc ， Rb2 and Rd were comparable between the two standard decoctions. Compared with the standard decoction of the traditional decoction pieces， the average transfer rates of ginsenoside Rg1， Rb1， Rc， Rb2 and dry extract rate of the standard decoction of GRR decoction pieces produced by fresh cutting were significantly increased（P<0.05）， and the average transfer rate of ginsenoside Re and Rd also increased， but the difference was not statistically significant. ConclusionThe dry extract rate， content and transfer rate of index components of standard decoction of GRR decoction pieces produced by fresh cutting are better than those of the standard decoction of traditional decoction pieces， which can provides data support for the subsequent clinical application of fresh cutting products.
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Focusing on the development and quality improvement strategy of the traditional Chinese medicine(TCM) industry, the scientific and technological innovation of the new engineering of TCM should be paid attention to solve the "stuck neck" dilemma. Under the background of the ecological and industrial revolution of the scientific and technological innovation system, the super-scale information interaction and multi-dimensional integration will inevitably lead to profound changes in the manufacturing mode of TCM. Manufacturing measurement of TCM is formed on the basis of the reliability engineering theory of process control of TCM production. It is the development extension of system theory and system science ideas and a cross-fertilization discipline that combines theory with practice and adheres to the "four-oriented" re-epistemology improvement of the TCM discipline. In response to the problems of complex raw material sources, coarse process technology, unclear material basis, and poor applicability of equipment and technology in the manufacture of TCM, the transformation research mode of "aiming at the integration of pharmaceutical industry-developing intelligent production line-enabling industrial transformation" has been developed. This paper proposed the four key engineering technical problems, i.e., the identification of critical quality attributes(CQA) in the manufacture of TCM, the quality by design(QbD) and product development of the manufacturing process of TCM, the quality transfer principle and multivariate process capability index of TCM manufacturing, and the development of measurement technology and equipment of the manufacturing measurement of TCM, to achieve the systematization of quality control indicators, real-time process control, digitalization of manufacturing process, transparency of quality transfer, and intelligent whole-process control. In this paper, the new concepts, new theories, and new technologies provide a reference for the industrialization of TCM.
Subject(s)
Medicine, Chinese Traditional , Reproducibility of Results , Commerce , Drug Industry , Quality ControlABSTRACT
Traditional Chinese medicine （TCM） is the treasure of the Chinese nation. As an important raw material for clinical treatment of diseases， Chinese materia medica plays an extremely important role. However， in the process of transformation from traditional wild collection of animals and plants to modern artificial cultivation and industrial production of preparations， whether the quality of Chinese materia medica is fully transferred will directly affect the quality and clinical efficacy of Chinese materia medica preparation. From the field to the sickbed， process control of quality transfer of Chinese materia medica is the key to guarantee quality and curative effect. In this paper， the whole process that affects the quality of Chinese materia medica preparations such as seed and seedling， planting and breeding， harvesting and processing， processing of decoction pieces and preparation production was analyzed. Paying attention to the whole process of quality control of Chinese materia medica is of great significance to improve the quality of Chinese materia medica preparations and promote the rapid development of TCM. Based on this， the author intended to analyze the key control links in the quality transfer process of Chinese materia medica （breeding， planting areas and field management， timely harvesting and intensive primary processing， appropriate processing， optimization of preparation technology， standardization of packaging and informationization of storage and transportation）， in order to provide reference for the design and development of Chinese materia medica preparations guided by clinical value.
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Lonicerae Japonicae Flos and Artemisiae Annuae Herba(LA or Jinqing) alcohol precipitation has various process parameters and complex process mechanism, and is one of the key units for manufacturing Reduning Injection. In order to identify the critical process parameters(CPPs) affecting the weight of the extract produced from the alcohol precipitation process, 259 batches of historical production data from 2017 to 2018 were collected, with a total of 829 318 data points. These data showed characteristics of large data, such as a large data volume, a low value density, and diverse sources. The data cleaning and feature extraction were first performed, and 48 feature variables were selected. The original data points were reduced to 9 936. Then, a combination of Pearson correlation analysis and grey correlation analysis were used to screen out 15 potential critical process parameters(pCPPs). After that, the partial least squares(PLS) was used in prediction of the weight of the extract, proving that the performance of predictive model based on 15 pCMAs is equivalent to that of predictive model based on 48 feature variables. The variable importance in projection(VIP) index was used to identify 9 CPPs, including 2 alcohol precipitation supernatant volume parameters, 4 initial extract weight parameters and 3 added alcohol volume parameters. As a result, the number of data points was 1 863, accounting for 0.28% of the original data. The big data analysis approach from a holistic point of view can effectively increase the value density of the original data. The critical process parameters obtained can help to accurately describe the quality transfer mechanism of the Jinqing alcohol precipitation process.
Subject(s)
Alcohols , Big Data , Drugs, Chinese Herbal/chemistry , Solvents , Technology, PharmaceuticalABSTRACT
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.
Subject(s)
Algorithms , Big Data , Commerce , Data Mining , Medicine, Chinese Traditional , Quality Control , Technology, PharmaceuticalABSTRACT
Objective: To study the correlation between the apparent color of the samples and the important variable components of HPLC fingerprint of rice-processed Codonopsis Radix (rpCR) in processing and its quality transfer law, and lay the foundation for revealing the processing principle of rpCR. Methods: This experiment was based on the experience of the process of rpCR and the apparent color change of traditional processed slices, the visual analyzer was used to analyze the change of apparent color of rpCR from different process time. HPLC fingerprint was used to evaluate the dynamic changes of chemical constituents of rpCR in processing. Then, the multivariate statistical method was used to analyze the correlation between the apparent color and the important variable components of the HPLC fingerprint. Results: In the processing of rpCR, the total color value (E*) of sample powder showed a downward trend, the apparent color of the samples changed from light yellowish brown to dark yellow; The proportions of the 10 chemical components varied greatly, corresponding to peaks of 7, 9, 10, 2, 3, 1, 20, 15, 6, and 4 in HPLC fingerprint, among them peak 4 was confirmed to be 5-hydroxymethyl-2-furaldehyde; Components 1, 3 and 4 were highly significantly and negatively relevant with the change of total color value Eab*, and peak 2 was highly significantly and positively correlated with the change of total color value Eab*, while peak 6 and peak 15 were positively relevant with the change of total color value Eab*. Conclusion: Compounds 1, 2, 3, 4, 6, and 15 were the components with obvious changes in process of rpCR, which were significantly correlated with the change of color and could be used as chemical markers for the monitoring processing and quality control of rpCR.