A New Approach to Network Pharmacological Analysis Based on Key Pathophysiological Processes
10.13422/j.cnki.syfjx.20230814
- VernacularTitle:基于关键病理生理学过程的网络药理学分析新思路
- Author:
Yizhi YAN
1
;
Chaoya LI
2
;
Manfei DENG
1
;
Peng ZENG
1
Author Information
1. School of Basic Medicine， Hengyang Medical College， University of South China， Hengyang 421001， China
2. Chenzhou No. 1 People's Hospital， Chenzhou 423000， China
- Publication Type:Journal Article
- Keywords:
complex diseases;
key pathophysiological processes;
network pharmacology analysis;
new ideas;
Alzheimer’s disease
- From:
Chinese Journal of Experimental Traditional Medical Formulae
2023;29(17):203-211
- CountryChina
- Language:Chinese
-
Abstract:
In recent years， the field of network pharmacology （NP） has developed rapidly， but the flawed and routine workflow has seriously affected the scientificity and reliability of NP analysis results. For complex diseases caused by environmental and genetic factors， symptomatic treatment or drugs targeting a single pathophysiological process cannot prevent or delay the progression of the disease， so the drug development fails or withdraws from the market. Therefore， there is an urgent need to develop new ideas for NP analysis that combines multiple pathophysiological processes. The key pathophysiological process is an important and complete set of pathological changes in the process of the occurrence， development， and outcome of the disease， which represents the current comprehensive and profound understanding of the nature of the disease. In order to improve the quality of NP research and promote the healthy development of the NP field， this paper proposes a new idea of NP analysis based on key pathophysiological processes. Based on the long-term clinical practice of traditional Chinese medicine and the key pathophysiological process of the disease， the method comprehensively analyzes the pharmacological mechanism and active ingredients of traditional Chinese medicine compound from the perspective of key pathophysiological process， which increases the scientifically， reliability， and repeatability of the analysis results. This paper takes Alzheimer's disease （AD） as an example to illustrate the necessity， feasibility， main workflow， advantages， and disadvantages of this method， and it is expected to screen disease-modifying drugs that prevent or reverse the course of the disease and promote the clinical transformation of research results.
