Data mining in traditional Chinese medicine product quality review / 中国中药杂志

The traditional Chinese medicine(TCM) enterprises have accumulated a large amount of product quality review(PQR) data. Mining these data can reveal the hidden knowledge in production and helps improve pharmaceutical manufacturing technology. However, there are few studies involving the mining of PQR data and thus enterprises lack the guidance to analyze the data. This study proposed a method to mine the PQR data, which consisted of 4 functional modules: data collection and preprocessing, risk classification of variables, risk evaluation by batches, and the regression analysis of quality. Further, we carried out a case study of the formulation process of a TCM product to illustrate the method. In the case study, the data of 398 batches of products during 2019-2021 were collected, which contained 65 process variables. The risks of variables were classified according to the process performance index. The risk of each batch was analyzed through short-term and long-term evaluation, and the critical variables with the strongest impact on the product quality were identified by partial least square regression. The results showed that 1 variable and 13 batches were of high risk, and the critical process variable was the quality of the intermediates. The proposed method enables enterprises to comprehensively mine the PQR data and helps to enhance the process understanding and improve the quality control.

Methodology and application of process analytical technology (PAT) for traditional Chinese medicine manufacturing:a review / 中国中药杂志

Owing to the advancement in pharmaceutical technology, traditional Chinese medicine industry has seen rapid development. Preferring conventional manufacturing mode, pharmaceutical enterprises of traditional Chinese medicine have no effective process detection tools and process control methods. As a result, the quality of the final products mainly depends on testing and the quality is inconsistent in the same batch. Process analytical technology(PAT) for traditional Chinese medicine manufacturing, as one of the key advanced manufacturing techniques, can break through the bottleneck in quality control of medicine manufacturing, thus improving the production efficiency and product quality and reducing the material and energy consumption. It is applicable to the process control and real-time release of advanced manufacturing modes such as intelligent manufacturing and continuous manufacturing. This paper summarized the general idea of PAT for traditional Chinese medicine manufacturing. Through the analysis of the characteristics and status quo of the technology, we summed up the methodology for the continuous application and improvement of PAT during the whole life-cycle of traditional Chinese medicine. The five key procedures(process understanding, process detection, process modeling, process control, and continuous improvement) were summarized, and the application was reviewed. Finally, we proposed suggestions for the technical and regulatory challenges in implementing PAT in traditional Chinese medicine industry. This paper aims to provide a reference for development and application of PAT in advanced manufacturing, intelligent manufacturing, and continuous manufacturing of traditional Chinese medicine industry.

Methodology for adaptive decision--making research on manufacturing process of traditional Chinese medicine based on deep reinforcement learning / 中国中药杂志

The manufacturing process of traditional Chinese medicine is subject to material fluctuation and other uncertain factors which usually cause non-optimal state and inconsistent product quality. Therefore, it is necessary to design and collect the quality-rela-ted physical parameters, process parameters, and equipment parameters in the whole manufacturing process of traditional Chinese medicine for digitization and modeling of the process. In this paper, a method for non-optimal state identification and self-recovering regulation was developed for active quality control in the manufacturing process of traditional Chinese medicine. Moreover, taking vacuum belt drying process as an example, a DQN algorithm-based intelligent decision model was established and verified and the implementation process was also discussed and studied. Thus, the process parameters-based self-optimization strategy discovery and path planning of optimal process control were rea-lized in this study. The results showed that the deep reinforcement learning-based artificial intelligence technology was helpful to improve the product quality consistency, reduce production cost, and increase benefit.

Digital twin based key technologies for intelligent manufacturing of traditional Chinese medicine / 中国中药杂志

In this paper, we first introduced the concept of digital twin(DT) based key technologies for intelligent manufacturing of traditional Chinese medicine(TCM) and applied DT in two case studies of novel extraction equipment for traditional Chinese medicine and drying equipment for Chinese medicine pills to illustrate the advantages of DT in development of new pharmaceutical technology and optimization of pharmaceutical equipment structure. Furthermore, we discussed the feasibility to adopt DT in the production process of TCM for formation of data-driven real-time optimization of production process and dynamic prediction `of operation and maintenance service. The "ruled" production mode based on data and driven by algorithm was constructed to realize the technical scheme of quality perception, evaluation, prediction, intelligent control and intelligent decision-making in product life cycle.

Near infrared spectroscopy based process trajectory technology and its application in monitoring and controlling of traditional Chinese medicine manufacturing process / 中国中药杂志

In this paper, the principle of NIRS (near infrared spectroscopy)-based process trajectory technology was introduced.The main steps of the technique include:① in-line collection of the processes spectra of different technics; ② unfolding of the 3-D process spectra;③ determination of the process trajectories and their normal limits;④ monitoring of the new batches with the established MSPC (multivariate statistical process control) models.Applications of the technology in the chemical and biological medicines were reviewed briefly. By a comprehensive introduction of our feasibility research on the monitoring of traditional Chinese medicine technical process using NIRS-based multivariate process trajectories, several important problems of the practical applications which need urgent solutions are proposed, and also the application prospect of the NIRS-based process trajectory technology is fully discussed and put forward in the end.