RESUMO
As China is implementing the policy of "Announcement on Ending the Pilot Work of Chinese medicine formula gra-nules", the standard of Chinese medicine formula granules has gradually become the focus of industry development. Up to now, 196 national drug standards for Chinese medicine formula granules have been published by China, which guaranteed the production quality of Chinese medicine formula granules. However, there are still several challenges such as the rational application of national drug standards and the enrichment and improvement of varieties. The basic content of the issued national drug standards for Chinese medicine formula granules was analyzed and compared with the quality standard provisions of the corresponding decoction pieces in the Chinese Pharmacopoeia(2020 edition) in this paper. This paper discussed the main characteristics of paste-forming rate of each medicinal raw materials, "quantity-quality" transformation, equivalent ratio, and so on, and clarified the characteristics of the national standard for Chinese medicine formula granules. This paper provided references for achieving the unified quality control and meeting the overall quality requirements of Chinese medicine formula granules.
Assuntos
Medicamentos de Ervas Chinesas , Medicina Tradicional Chinesa , China , Controle de QualidadeRESUMO
Chinese medicine dispensing granules, the result of the efforts to transform Chinese medicinal decoction pieces in China, features portability and ease of storage. Thus, it is destined to be an indispensible dosage form in the modernization drive of Chinese medicine. The Announcement on Ending the Pilot Project of Chinese Medicine Dispensing Granules was released in February 2021 and relevant regulations went into force in November 2021, which marks the a new journey for the development of Chinese medicine dispensing granules and the beginning of the "post-pilot era". However, it faces the challenges in quality and standard. This study reviewed the history of Chinese medicine dispensing granules, analyzed the technical progress, market, and main problems in development, and proposed suggestions and prospects for its development in the "post-pilot era", which is expected to serve as a reference for its industry development and rational use.
Assuntos
Medicamentos de Ervas Chinesas , Medicina Tradicional Chinesa , China , Medicamentos de Ervas Chinesas/uso terapêutico , Desenvolvimento Industrial , Projetos PilotoRESUMO
The quality of traditional Chinese medicine tablets is correlated with clinical efficacy and drug safety, and plays a great role in promoting the development of traditional Chinese medicine. However, the existing traditional artificial identification and modern instrument detection in terms of accuracy and timeliness have both advantages and disadvantages. Therefore, how to quickly and accurately identify the quality of traditional Chinese medicine tablets has become a high-profile issue. The purpose of this paper is to explore the feasibility of the application of electronic eye technology in the study of rapid identification of traditional Chinese medicine quality. A total of 80 batches of samples were collected and tested by Fritillariae Cirrhosae Bulbus for traditional empirical identification(M_1) and modern pharmacopeia(M_2). The optical data was collected from electronic eyes, and the chemical metrology was used to establish suitable discrimination models(M_3). Four authenticity and commodity specification models, namely identification analysis(DA), minimum bidirectional support vector machine(LS-SVM), partial minimum two-multiplier analysis(PLS-DA), main component analysis identification analysis(PCA-DA), were established, respectively. The accuracies of the authenticity identification models were 82.5%, 90.0%, 96.2% and 93.8%, while the accuracies of the commodity specification identification models were 89.3%, 96.0%, 90.7% and 97.3%, respectively. The models were well judged, the authenticity identification was based on the final identification model of PLS-DA, and the commodity specification was based on the final identification model of PCA-DA. There was no significant difference between its accuracy and M_1, and the time of determination was much shorter than M_2(P<0.01). Therefore, electronic-eye technology could be used for the rapid identification of the quality of Fritillariae Cirrhosae Bulbus.
Assuntos
Medicamentos de Ervas Chinesas , Fritillaria , Medicina Tradicional Chinesa , Raízes de Plantas , TecnologiaRESUMO
This study aims to explore the change laws of water absorption in Chinese herbal pieces and establish the prediction model of relative density for Chinese medicine compound decoction. Firstly, fitted equations of water absorption and decocting time was established by observing the change laws of water absorption in 36 kinds of Chinese herbal pieces in 12 groups(according to the drug-parts) with decocting time. The r value of the mineral group and other type group was 0.691 2 and 0.663 3, respectively. The r value of the remaining 10 groups was 0.802 2-0.925 4. All P values were less than 0.05(n=21). The formula of the amount of water added was optimized by combining the fitted equations with determined water absorption, and the liquid yield could be controlled in a range of 100%±10%. Secondly, it was determined that the liquid density tester could be used for the rapid determination of relative density of Chinese medicine decoction after methodological study and comparison with the pycnometer method. The linear regression equation between the corrected relative density(y) and extraction ratio(%, x) was built by measuring and analyzing the related parameters such as liquid yield, relative density and extraction ratio in 46 kinds of Chinese herbal pieces. The established equation was y=0.041 3x+1.003 7, r=0.930 9(P <0.01, n=46), with linear range of 1.94%-65.75%. Based on this, the prototype model for predicting relative density of Chinese medicine decoction was established, and the relative densities of 8 Chinese medicine decoctions were within the prediction interval of this model in verification. This study lays a foundation for database construction of Chinese medicine decoction, implementation of personalized decocting mode and rapid quality control of Chinese medicine decoction.
Assuntos
Medicamentos de Ervas Chinesas , Medicina Tradicional Chinesa , Controle de Qualidade , Gravidade Específica , ÁguaRESUMO
Traditional Chinese medicine( TCM) decoction contains complex bitterness. In this paper,the simple mixing of TCM monomer bitter substances is used as the entry point to study the law of bitterness superposition. With berberine hydrochloride( alkaloids),geniposide( terpenoids),and arbutin( glycosides) as mother liquor,sophoridine( alkaloids),gentiopicroside( terpenoids),and puerarin( glycosides) as additive substances,these different additive substances were mixed with different mother liquor according to concentration gradients to form different liquid mixtures. The bitterness of the additive solution and the mixtures was evaluated by traditional human taste panel method( THTPM) and electronic tongue; the bitterness-concentration fitting model of the additive solution and the liquid mixtures was established by Weibull and logarithmic curves. By comparing and analyzing the bitterness-concentration model and the bitterness difference( ΔI_0/ΔI_e) of the additive solution and the mixture,the influence of mother liquor on the bitterness of the mixture was investigated. The results showed that both the additive solution bitterness model and the liquid mixture bitterness model were consistent with the Weibull model and the logarithmic model( THTPM: R~2≥0. 887 0,P<0. 01; electronic tongue test:R~2≥0. 753 2,P<0. 05). The fitting degree of the Weibull model was generally higher than that of the logarithmic model; the bitterness difference( ΔI_0) was monotonously decreasing; the fitting equation of tongue bitterness and electronic tongue bitterness: R~2≥0. 874 2,P<0. 01. In this article,through the superposition of different kinds of TCM bitter substances,THTPM and electronic tongue test was combined. It was found that the bitterness after superposition was still in Weibull or logarithmic relationship with the concentration of additive substances; THTPM showed that the effect of bitter mother liquor on the bitterness of the mixture decreased with the increase of the concentration of the additive; the bitterness of the electronic tongue was obviously related to the bitterness of THTPM. However,further verification is needed later by optimizing the concentration gradient and expanding the sample size.
Assuntos
Nariz Eletrônico , Medicina Tradicional Chinesa , Paladar , Alcaloides/análise , Glicosídeos/análise , Humanos , Terpenos/análiseRESUMO
This paper focuses on determining the authenticity and identifying the species of Fritillariae cirrhosae using electronic nose, electronic tongue, and electronic eye sensors, near infrared and mid-level data fusion. 80 batches of Fritillariae cirrhosae and its counterfeits (including several batches of Fritillaria unibracteata Hsiao et K.C. Hsia, Fritillaria przewalskii Maxim, Fritillaria delavayi Franch and Fritillaria ussuriensis Maxim) were initially identified by Chinese medicine specialists and by criteria in the 2020 edition of Chinese Pharmacopoeia. After obtaining the information from several sensors we constructed single-source PLS-DA models for authenticity identification and single-source PCA-DA models for species identification. We selected variables of interest by VIP value and Wilk's lambda value, and we subsequently constructed the three-source fusion model of intelligent senses and the four-source fusion model of intelligent senses and near-infrared spectroscopy. We then explained and analyzed the four-source fusion models based on the sensitive substances detected by key sensors. The accuracies of single-source authenticity PLS-DA identification models based on electronic nose, electronic eye, electronic tongue sensors and near-infrared were respectively 96.25%, 91.25%, 97.50% and 97.50%. The accuracies of single-source PCA-DA species identification models were respectively 85%, 71.25%, 97.50% and 97.50%. After three-source data fusion, the accuracy of the authenticity identification of the PLS-DA identification model was 97.50% and the accuracy of the species identification of the PCA-DA model was 95%. After four-source data fusion, the accuracy of the authenticity of the PLS-DA identification model was 98.75% and the accuracy of the species identification of the PCA-DA model was 97.50%. In terms of authenticity identification, four-source data fusion can improve the performance of the model, while for the identification of the species the four-source data fusion failed to optimize the performance of the model. We conclude that electronic nose, electronic tongue, electronic eye data and near-infrared spectroscopy combined with data fusion and chemometrics methods can identify the authenticity and determine the species of Fritillariae cirrhosae. Our model explanation and analysis can help other researchers identify key quality factors for sample identification. This study aims to provide a reference method for the quality evaluation of Chinese herbs.
RESUMO
Introduction: We here describe a new method for distinguishing authentic Bletilla striata from similar decoctions (namely, Gastrodia elata, Polygonatum odoratum, and Bletilla ochracea schltr). Methods: Preliminary identification and analysis of four types of decoction pieces were conducted following the Chinese Pharmacopoeia and local standards. Intelligent sensory data were then collected using an electronic nose, an electronic tongue, and an electronic eye, and chromatography data were obtained via high-performance liquid chromatography (HPLC). Partial least squares discriminant analysis (PLS-DA), support vector machines (SVM), and back propagation neural network (BP-NN) models were built using each set of single-source data for authenticity identification (binary classification of B. striata vs. other samples) and for species determination (multi-class sample identification). Features were extracted from all datasets using an unsupervised approach [principal component analysis (PCA)] and a supervised approach (PLS-DA). Mid-level data fusion was then used to combine features from the four datasets and the effects of feature extraction methods on model performance were compared. Results and Discussion: Gas chromatography-ion mobility spectrometry (GC-IMS) showed significant differences in the types and abundances of volatile organic compounds between the four sample types. In authenticity determination, the PLS-DA and SVM models based on fused latent variables (LVs) performed the best, with 100% accuracy in both the calibration and validation sets. In species identification, the PLS-DA model built with fused principal components (PCs) or fused LVs had the best performance, with 100% accuracy in the calibration set and just one misclassification in the validation set. In the PLS-DA and SVM authenticity identification models, fused LVs performed better than fused PCs. Model analysis was used to identify PCs that strongly contributed to accurate sample classification, and a PC factor loading matrix was used to assess the correlation between PCs and the original variables. This study serves as a reference for future efforts to accurately evaluate the quality of Chinese medicine decoction pieces, promoting medicinal formulation safety.