Data mining in traditional Chinese medicine product quality review / 中国中药杂志
China Journal of Chinese Materia Medica
;
(24): 1264-1272, 2023.
Artigo
em Chinês
| WPRIM
| ID: wpr-970597
ABSTRACT
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.
Texto completo:
DisponíveL
Índice:
WPRIM (Pacífico Ocidental)
Assunto principal:
Controle de Qualidade
/
Medicamentos de Ervas Chinesas
/
Tecnologia Farmacêutica
/
Mineração de Dados
/
Medicina Tradicional Chinesa
Idioma:
Chinês
Revista:
China Journal of Chinese Materia Medica
Ano de publicação:
2023
Tipo de documento:
Artigo
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