A smart near-infrared spectroscopy evaluation system for quality management of Chinese medicinal materials based on quality markers
10.16438/j.0513-4870.2018-0770
- VernacularTitle:基于中药质量标志物构建中药材品质的近红外智能评价体系
- Author:
Gang BAI
1
;
Yuan-yuan HOU
1
;
Guo-yu DING
1
;
Min JIANG
1
;
Jie GAO
1
;
Tie-jun ZHANG
2
;
Chang-xiao LIU
2
Author Information
1. College of Pharmacy and Tianjin Key Laboratory of Molecular Drug Research, Nankai University, Tianjin 300353, China; State Key Laboratory of Medicinal Chemical Biology, Nankai University, Tianjin 300353, China
2. Research Center of TCM Quality Marker, Tianjin Institute of Pharmaceutical Research, Tianjin 300193, China; State Key Laboratory of Drug Delivery and Pharmacokinetics, Tianjin Institute of Pharmaceutical Research, Tianjin 300193, China
- Publication Type:Research Article
- Keywords:
Chinese medicinal materials;
quality marker;
near-infrared spectroscopy;
TCM quality management;
intelligent evaluation
- From:
Acta Pharmaceutica Sinica
2019;54(2):197-203
- CountryChina
- Language:Chinese
-
Abstract:
The quality of traditional Chinese medicine (TCM) is the lifeline for TCM industry. The development of artificial intelligence (AI) has provided new means for the quality management of Chinese medicinal materials (CMM). In this paper, we take the quality marker (Q-marker) as a breakthrough point, focused on the research strategy from chemical markers to Q-markers, picked up the characteristics of the Q-markers from the near infrared spectrum (NIRS), and explored the feasibility of establishing the NIRS assay based on Q-marker. After integrated the biological activity detection and artificial neural network algorithm, we try to establish the relationship between the spectral properties of NIRS and specific efficacy of the CMM. Finally, the bottlenecks will be solved that related to the transmission and traceability of quality attributes in the process of TCM production, quantity change, overall quality management and so on. This system is going to improve TCM quantity scientific and intelligent supervision, and promote the upgrading of traditional TCM industry.
