Traditional Chinese Medicine (TCM), which originated in ancient China with a history of thousands of years, characterizes and addresses human physiology, pathology, and diseases diagnosis and prevention using TCM theories and Chinese herbal products. Recently, the World Health Organization included TCM in the global diagnostic compendium, which marks the international recognition of TCM in global health care. In light of this, many research works have been devoted to revealing the effectiveness and efficacy of Chinese herbs for new drug discovery in a bottom-up manner. However, the pharmacological principles in TCM theory, the core treasure house of TCM, have rarely been systematically investigated in a top- down manner, which hinders the modernization and standardization of TCM. In this proposal, we will propose a novel TCM-based network pharmacology framework to discern general patterns and principles of human disease and predict herb-diseases associations. Specifically, we will construct an integrative database and pharmacological network of TCM through extensively collecting and cleaning large-scale TCM prescription data from ancient books, modern literature, and existing TCM data resources. Various topological and structural properties of the TCM pharmacological network will be systematically characterized to decipher the pharmacological principles of TCM theory. Based on the TCM pharmacological network, we will uncover the human disease-disease relationship and build an in-silico network-based pipeline for the prediction of drug-disease associations. Our project will promote the quantitative underpinning of TCM pharmacological principles, provide a basis for the objectification of the diagnosis and treatment process of Chinese medicine, and pave the way for the knowledge fusion of TCM evidence-based medicine and modern biology.
|Effective start/end date||1/06/23 → 31/05/26|
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