Traditional Chinese medicines (TCM), in “multi-component, multi-target, multi-pathway” paradigm, show satisfactory clinical results in complex diseases. Network pharmacology provides a novel paradigm to uncover and visualize the underlying interaction networks of TCMs against multifactorial diseases. The development and application of Network pharmacology has promoted the safety, efficacy, and mechanism investigations of TCMs, which then reinforces the credibility and popularity of TCMs. In the past decades, with the advent of advanced and intelligent technologies (such as metabolomics, proteomics, transcriptomics, single-cell omics, and artificial intelligence), Network pharmacology has been improved and deeply implemented and presented its great value and potential as the next drug-discovery paradigm. This talk briefly summarizes the recent research progress on Transcriptomics-based Network pharmacology application in TCMs for efficacy research, mechanism elucidation, target prediction, safety evaluation, drug repurposing, and drug design.
A Wed, study studied this question.