Original end-to-end smart diagnosis framework of systematic critical quality attributes meets FDA standards of phytomedicine by biosensor and multi-information fusion coupled with AI algorithm-Reference-Cited by-同舟云学术

Original end-to-end smart diagnosis framework of systematic critical quality attributes meets FDA standards of phytomedicine by biosensor and multi-information fusion coupled with AI algorithm

Published:2023 Issue:1 Volume:25 Page:384-398
ISSN:1463-9262
Container-title:Green Chemistry
language:en
Short-container-title:Green Chem.

Author:

Ma Chaofu¹,Ma Lijuan¹,Wang Zijian²,Li Nan¹,Li Mingshuang¹,Wang Jing¹,Wang Xiaomeng¹,Song Xiao³,Yan Hao³,Han Yanyu¹,Guan Yongxia⁴,Yao Jingchun⁴,Zhang Guimin⁴,Wu Zhisheng¹⁵^ORCID

Affiliation:

1. Beijing University of Chinese Medicine, School of Chinese materia medica, Beijing 100029, China

2. Beijing Tongrentang Group Co., Ltd, Beijing 100062, China

3. Shaanxi University of Chinese Medicine, Coll Pharm, Xianyang 712046, China

4. Lunan Pharmaceutical Group Co., Ltd, State Key Laboratory of generic technology of traditional Chinese Medicine, Linyi 276005, China

5. Engineering Research Center for Pharmaceutics of Chinese Materia Medica and New Drug Development, Ministry of Education, Beijing 100029, China

Abstract

Original end-to-end smart diagnosis framework of systematic critical quality attributes for green manufacturing of phytomedicine.

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Special Project for Research and Development in Key areas of Guangdong Province

Fundamental Research Funds for the Central Universities

National Outstanding Youth Science Fund Project of National Natural Science Foundation of China

Publisher

Royal Society of Chemistry (RSC)

Subject

Pollution,Environmental Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2023/GC/D2GC03835H

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