[Optimization of prediction model for personalized water pills based on semantic analysis of traditional Chinese medicine materials].

This study aims to optimize the prediction model of personalized water pills that has been established by our research group. Dioscoreae Rhizoma, Leonuri Herba, Codonopsis Radix, Armeniacae Semen Amarum, and calcined Oyster were selected as model medicines of powdery, fibrous, sugary, oily, and brittle materials, respectively. The model prescriptions were obtained by uniform mixing design. With hydroxypropyl methylcellulose E5(HPMC-E5) aqueous solution as the adhesive, personalized water pills were prepared by extrusion and spheronizaition. The evaluation indexes in the pill preparation process and the multi-model statistical analysis were employed to optimize and evaluate the prediction model of personalized water pills. The prediction equation of the adhesive concentration was obtained as follows: Y_1=-4.172+3.63X_A+15.057X_B+1.838X_C-0.997X_D(adhesive concentration of 10% when Y_1<0, and 20% when Y_1>0). The overall accuracy of the prediction model for adhesive concentration was 96.0%. The prediction equation of adhesive dosage was Y_2=6.051+94.944X_A~(1.5)+161.977X_B+70.078X_C~2+12.016X_D~(0.3)+27.493X_E~(0.3)-2.168X_F~(-1)(R~2=0.954, P<0.001). Furthermore, the semantic prediction model for material classification of traditional Chinese medicines was used to classify the materials contained in the prescription, and thus the prediction model of personalized water pills was evaluated. The results showed that the prescriptions for model evaluation can be prepared with one-time molding, and the forming quality was better than that established by the research group earlier. This study has achieved the optimization of the prediction model of personalized water pills.

[Composite excipients for preparing concentrated water pills of personalized traditional Chinese medicine prescriptions by extruding-rounding method].

This study aims to optimize the composite excipients suitable for the preparation of concentrated water pills of personalized traditional Chinese medicine prescriptions by the extruding-rounding method and investigate the roles of each excipient in the preparation process. The fiber materials and powder materials were taken as the standard materials suitable as excipients in the preparation of personalized concentrated water pills without excipient. Water absorption properties and torque rheology were used as indicators for selecting the materials of composite excipients. The ratio of composite excipients was optimized by D-optimal mixture design. Moreover, to demonstrate the universal applicability of the optimal composite excipients, this study selected three traditional Chinese medicine prescriptions with low, medium, and high extraction rates to verify the optimal ratio. Finally, the effects of each selected excipient on the molding of personalized concentrated water pills were investigated with the four parameters of the pill molding quality as indicators. The optimized composite excipients were dextrin∶microcrystalline cellulose(MCC)∶low-substituted hydroxypropyl cellulose(L-HPC) at a ratio of 1∶2∶4. The composite excipients were used for the preparation of personalized concentrated water pills with stable process, good quality, and a wide range of application. Dextrin acted as a diluent and accelerated the speed of extruding. MCC mainly served as an adhesive, increasing the cohesion and viscosity of the pills. L-HPC as a water absorbent and disintegrating agent can absorb and hold the water of the concentrate and has a strong disintegration effect.

[Research practice and development direction of intelligent manufacturing of presonalized traditional Chinese medicine preparations].

In recent years, as people's living standards continue to improve, and the pace of life accelerates dramatically, the demand and quality of traditional Chinese medicine(TCM) services from patients continue to rise. As an essential supplement to the existing forms of TCM application, such as Chinese patent medicine, decoction, and formulated granules, presonalized TCM preparations is facing an increasing market demand. Currently, manual and semi-mechanized production are the primary production ways in presonalized TCM preparations. However, the production process control level is low, and digitalization and informatization need to be improved, which restricts the automated and intelligent development of presonalized TCM preparations. Presonalized TCM preparations faces a significant opportunity and challenge in integrating with intelligent manufacturing through research and development of intelligent equipment and core technology. This paper overviews the connotation and characteristics of intelligent manufacturing and summarizes the application of intelligent manufacturing technologies such as "Internet of things" "big data", and "artificial intelligence" in the TCM industry. Based on the innovative research and development model of "intelligent classification of TCM materials, intelligent decision making of prescription and process, and online control and intelligent production" of presonalized TCM preparations, the research practice and achievements from our research group in the field of intelligent manufacturing of presonalized TCM preparations are introduced. Ultimately, the paper proposes the direction for developing intelligent manufacturing of presonalized TCM preparations, which will provide a reference for the research and application of automation and intelligence of presonalized TCM preparations.

[Molding law of traditional Chinese medicine gel plaster based on physicochemical properties of raw materials and intermediates].

This paper aims to study the correlation between the physicochemical properties of raw materials and intermediates and the molding quality and law of traditional Chinese medicine(TCM) gel plaster by using TCM slices and powder as raw materials. 48 TCM compounds are selected as model prescriptions to prepare gel plasters. The rotational rheometer is used to determine the rheological parameters of the plaster, including storage modulus(G'), loss modulus(G″), yield stress(τ), and creep compliance [J(t)]. The molding quality of the prepared TCM gel plaster is evaluated by subjective and objective measures. Clustering and principal component analysis are conducted to evaluate the physical properties of the plaster. By measuring the rheological properties of the plaster, the molding quality of the TCM gel plaster can be predicted, with an accuracy of 83.72% after seven days of modeling and 88.37% after 30 days of modeling. When the parameters such as G' and G″ of the plaster are large, and the [J(t)] is small, the molding quality of the plaster is better. When the plaster coating point is no less than 3, it is difficult to be coated. In addition, when the proportion of metal ions in the prescription is higher, the 30-day forming quality of the plaster is mainly affected, and the viscosity of the plaster is poor. If the prescription contains many acidic chemical components, the 7-day forming quality of the plaster is mainly affected, with many residuals. The results suggest that the rheological properties of the plaster can be used to predict the molding quality of TCM slice and powder gel plaster. It can provide a reference for the development of TCM gel plaster prescriptions.

[Intelligent material classification of traditional Chinese medicine based on semantic analysis].

A method for material classification of traditional Chinese medicines based on the physical properties of powder has been established by our research group. This method involves pre-treatment of traditional Chinese medicine decoction pieces, powder preparation, and determination of physical properties, being cumbersome. In this study, the word segmentation logic of semantic analysis was adopted to establish the thesaurus and local standardized semantic word segmentation database with the macroscopic and microscopic characteristics of 36 model traditional Chinese medicines as the basic data. The physical properties of these medicines have been determined and the classification of these medicines is clear in the cluster analysis. A total of 55 keywords for powdery, fibrous, sugary, oily, and brittle materials were screened by association rules and the set inclusion and exclusion criteria, and the weights of the keywords were calculated. Furthermore, the algorithms of the keyword matching scores and the computation rules of the single or multiple material classification were established for building the intelligent model of semantic analysis for the material classification. The semantic classification results of the other 35 TCMs except Pseudostellariae Radix(multi-material medicine) agreed with the clustering results based on the physical properties of the powder, with an agreement rate of 97.22%. In model validation, the prediction results of semantic classification of traditional Chinese medicines were consistent with the clustering results based on the physical properties of powder, with an agreement rate of 83.33%. The results showed that the method of material classification based on semantic analysis was feasible, which laid a foundation for the development of intelligent decision-making technology for personalized traditional Chinese medicine preparations.

[Molding matrix formulation of hot-melt pressure-sensitive adhesive plaster of personalized traditional Chinese medicine preparations].

This study aims to optimize the matrix formulation for the hot-melt pressure-sensitive adhesive plaster of personalized traditional Chinese medicine(TCM) preparations and verify the applicability of the formulation. The central composite design in JMP Pro 16.1.0 was employed to optimize the dosages of styrene-isoprene-styrene triblock copolymer(SIS), hydrogenated petroleum resin, and lightweight liquid paraffin, with the fine powder of Yipifang as the model drug(drug loading of 10%) and the sensory score and objective evaluation as the comprehensive evaluation indicators. The quality evaluation system of hot-melt pressure-sensitive adhesive plaster of personalized TCM preparations was established. The applicability of the optimized matrix formulation of hot-melt pressure-sensitive adhesive plaster was verified with 16 TCM preparations for external application. Furthermore, the applicability of the matrix formulation was investigated with different drug loadings. The general molding matrix formulation was SIS∶hydrogenated petroleum resin∶lightweight liquid paraffin 3∶3∶5. The optimized matrix formulation showed good molding properties and high quality scores for 16 TCM preparations and were suitable for the plastering of finely powdered decoction pieces with a loading capacity of 10% to 30%. The results suggest that the optimized matrix formulation has good applicability and is suitable for TCM preparations. The findings lay a foundation for the application and promotion of the hot-melt pressure-sensitive adhesive plasters of personalized TCM preparations.

[Preparation process selection of presonalized traditional Chinese medicine concentrated watered pills containing heat-unstable components].

In the process of preparing presonalized concentrated watered pills, the decoction needs to be concentrated by heat and mixed with medicinal slices or powder to prepare a wet mass. However, some of the traditional Chinese medicine(TCM) components are easily decomposed or transformed by heat. In order to optimize the preparation process of presonalized TCM concentrated watered pills and reduce the loss of heat-unstable components in prescriptions, this study uses five compound TCM prescriptions containing heat-unstable components as model prescriptions, namely the Linggui Zhugan Formula, Xiaochengqi Formula, Sanpian Formula, Xiaoer Qixing Formula, and Xiaoyao Formula. Based on the two kinds of preparation process of presonalized concentrated watered pills previously established by our research group, whole extract concentrated watered pills and concentrated watered pills without excipients are prepared, respectively. Characteristic maps are measured and compared with those of the corresponding decoction. The results show that the characteristic maps of the concentrated watered pills without excipients of the five model prescriptions are very close to those of the decoction, and the number of characteristic peaks and peak areas are higher than those of whole extract concentrated watered pills. In addition, the peak area of some peaks is higher than that of the corresponding decoction. Thus, it is recommended to select the preparation process of prescription-based concentrated watered pills without excipients based on the "unification of medicines and excipients" to preserve those heat-unstable components more effectively when the prescription contains a heat-unstable component of TCM. This study provides a basis for the subsequent reasonable development and application of presonalized TCM pills.

[Classification optimization of traditional Chinese medicine materials based on additive physical properties of powder].

According to the method of predicting the physical properties of oily powder based on the additive physical properties of Chinese medicinal powder, Dioscoreae Rhizoma and calcined Ostreae Concha with high sieve rate and good fluidity were mixed and crushed with Persicae Semen, Platycladi Semen, Raphani Semen, Ziziphi Spinosae Semen, and other typical oily materials with high fatty oil content in proportion to obtain 23 mixed powders. Fifteen physical properties such as bulk density, water absorption, and maximum torque force were measured, and the physical properties of typical oily powders were predicted. When the mixing and grinding ratio was in the range of 5∶1-1∶1, the r value in the correlation equation between the weighted average score of the mixed powder and the powder proportion ranged from 0.801 to 0.986, and the linearity was good, indicating that the method of predicting the physical properties of oily powder based on the additive physical properties of traditional Chinese medicine(TCM)powder was feasible. The results of cluster analysis showed that the classification boundaries of the five kinds of TCM materials were clear, and the similarity of the physical fingerprints of powdery and oily materials decreased from 80.6% to 37.2%, which solved the problem of fuzzy classification boundaries of powdery and oily materials due to the lack of representativeness of oily material model drugs. The classification of TCM materials was optimized, laying a foundation for optimizing the prediction model of the prescription of personalized water-paste pills.