Network pharmacology: curing causal mechanisms instead of treating symptoms.
By Cristian Nogales, Zeinab M. Mamdouh, Markus List, Christina Kiel, A. I. Casas, Harald H. H. W. Schmidt. TIPS - Trends in Pharmacological Sciences, 2021
995 citations recorded by the source corpus.
For complex diseases, most drugs are highly ineffective, and the success rate of drug discovery is in constant decline. While low quality, reproducibility issues, and translational irrelevance of most basic and preclinical research have contributed to this, the current organ-centricity of medicine and the 'one disease-one target-one drug' dogma obstruct innovation in the most profound manner. Systems and network medicine and their therapeutic arm, network pharmacology, revolutionize how we define, diagnose, treat, and, ideally, cure diseases. Descriptive disease phenotypes are replaced by endotypes defined by causal, multitarget signaling modules that also explain respective comorbidities. Precise and effective therapeutic intervention is achieved by synergistic multicompound network pharmacology and drug repurposing, obviating the need for drug discovery and speeding up clinical translation.
Subfields: Computational Theory and Mathematics, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/5bed9300ca4b78d5ffa791cfaed3e07f96eff4b6
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Citations in the corpus
- Network pharmacology: towards the artificial intelligence-based precision traditional Chinese medicine (2023, background): “…and the research strategy of disease diagnosis and treatment has also shifted from ‘single disease, single target and single drug’ to ‘multi-target and systematic regulation’, emphasizing the importance of analyzing the mechanism of complex diseases from the perspective of systems biology [2, 3].”