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1.
China Journal of Chinese Materia Medica ; (24): 3127-3134, 2018.
Artigo em Chinês | WPRIM | ID: wpr-690407

RESUMO

In this work, we obtained the quality information of Panax notoginseng with near infrared spectroscopy in an efficient way. By combining the quality information of raw materials with process parameters in experimental design, quantitative relationship models were established between material quality information, process parameters and product quality of P. notoginseng, thus realizing the feedforward control of the alcohol extraction process. The quantitative models established have high robustness and satisfactory forecasting ability. With new batches of P. notoginseng introduced for the alcohol extraction process, the quality information of raw materials was rapidly obtained. Based on the established models, the process parameters were optimized according to the expected critical quality attributes (CQA), thereby reducing the fluctuation of product quality caused by raw material variation.

2.
Chinese Traditional and Herbal Drugs ; (24): 4560-4564, 2017.
Artigo em Chinês | WPRIM | ID: wpr-852437

RESUMO

As a widely applied process control strategy in chemical industry, the feedforward control strategies have been applied in pharmaceutical manufacturing to reduce the quality fluctuation of drugs. The application of feedforward control strategy in the manufacturing of Chinese materia medica (CMM) can help us to understand the relationship between input material attributes, process parameters and critical quality attributes (CQAs), and then to establish an optimal model for the adjustment of process parameters based on input material attributes with the aim of minimizing the variation of CQAs. Before the production of the new batch, the most suitable process parameters for the input materials can be calculated by the optimal model. The motivation of this paper is to provide an overview of recent research on application of feedforward control strategies in pharmaceutical manufacturing and demonstrate perspectives of their application in CMM.

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