Establishment of multiple evidence-integrated evaluation and prediction method for "toxic" Chinese medicines.
10.19540/j.cnki.cjcmm.20211129.601
- Author:
He-Rong CUI
1
;
Xiao-Yu ZHANG
1
;
Liang-Zhen YOU
1
;
Rui ZHENG
1
;
Zhao CHEN
1
;
Yin JIANG
1
;
Jing-Jing ZHANG
1
;
Hong-Cai SHANG
1
Author Information
1. Dongzhimen Hospital, Beijing University of Chinese Medicine Beijing 100700, China.
- Publication Type:Journal Article
- Keywords:
"toxic" Chinese medicine;
clinical feature;
evidence-based toxicology;
multiple evidence;
toxicity prediction
- MeSH:
Artificial Intelligence;
China;
Drugs, Chinese Herbal/pharmacology*;
Humans;
Medicine, Chinese Traditional;
Research Design;
Syndrome
- From:
China Journal of Chinese Materia Medica
2022;47(8):2266-2272
- CountryChina
- Language:Chinese
-
Abstract:
Traditional Chinese medicine(TCM) carries the experience and theoretical knowledge of the ancients, and the use of "toxic" Chinese medicines is a major feature and advantage of TCM. "Toxic" Chinese medicines have unique clinical value and certain medication risk under the guidance of TCM theories such as compatibility for detoxification and treatment based on syndrome differentiation. In recent years, the safety events of Chinese medicines have occurred frequently, which has made the safety of Chinese medicine a public concern in China and abroad. However, limited by conventional cognitive laws and technical methods, basic research on toxicity of Chinese medicines fails to be combined with the clinical application. As a result, it is difficult to identify the clinical characteristics of, predict toxic and side effects of, or form a universal precise medication regimen for "toxic" Chinese medicines, which restricts the clinical application of them. In view of the problem that the toxicity of "toxic" Chinese medicines is difficult to be predicted and restricts the clinical application, the evidence-based research concept will provide new ideas for safe applcation of them in clinical practice. The integrated development of multiple disciplines and techniques in the field of big data and artificial intelligence will also promote the renewal and development of the research models for "toxic" Chinese medicines. Our team tried to propose the academic concept of evidence-based Chinese medicine toxicology and establish the data-intelligence research mode for "toxic" Chinese medicines and the intelligent risk prediction method for medicinal combination in the early stage, which provided methodological supports for solving the above problem. Thus, on the basis of summarizing the research status and problems of the clinical medication regimen of "toxic" Chinese medicines, our team took the evidence-based toxicology of TCM as the core concept, and tried to construct the multiple-evidence integrated evaluation and prediction method for "toxic" Chinese medicine, so as to guide the establishment of the non-toxic medication regimen of "toxic" Chinese medicines. Specifically, through the analysis of multivariate data obtained from the basic research, the evidence-based toxicology database of Chinese medicines and the individualized "toxicity-effect" intelligent prediction platform were built based on the disease-syndrome virtual patients, so as to identify the clinical characteristics and risks of "toxic" Chinese medicines and develop individualized medication regime. This study is expected to provide a methodological reference for the establishment of medication regimen and risk prevention strategy for "toxic" Chinese medicines. The method established in this study will bridge clinical research and basic research, enhance the transformation of the scientific connotation of attenuated compatibility, promote the development of evidence-based Chinese medicine toxicology, and ensure the clinical safety of "toxic" Chinese medicines.
