Model informed precision medicine of Chinese herbal medicines formulas–A multi-scale mechanistic intelligent model

Yuanyuan Qian; Xiting Wang; Lulu Cai; Jiangxue Han; Zhu Huang; Yahui Lou; Bingyue Zhang; Yanjie Wang; Xiaoning Sun; Yan Zhang; Aisong Zhu

Journal of Pharmaceutical Analysis (Apr 2024)

Model informed precision medicine of Chinese herbal medicines formulas–A multi-scale mechanistic intelligent model

Yuanyuan Qian,
Xiting Wang,
Lulu Cai,
Jiangxue Han,
Zhu Huang,
Yahui Lou,
Bingyue Zhang,
Yanjie Wang,
Xiaoning Sun,
Yan Zhang,
Aisong Zhu

Affiliations

Yuanyuan Qian: Zhejiang Key Laboratory of Blood-Stasis-Toxin Syndrome, Zhejiang Chinese Medical University, Hangzhou, 310000, China; Zhejiang Engineering Research Center for “Preventive Treatment” Smart Health of Traditional Chinese Medicine, Zhejiang Chinese Medical University, Hangzhou, 310000, China; College of Basic Medical Sciences, Zhejiang Chinese Medical University, Hangzhou, 310000, China
Xiting Wang: Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, 100190, China
Lulu Cai: Zhejiang Key Laboratory of Blood-Stasis-Toxin Syndrome, Zhejiang Chinese Medical University, Hangzhou, 310000, China; Zhejiang Engineering Research Center for “Preventive Treatment” Smart Health of Traditional Chinese Medicine, Zhejiang Chinese Medical University, Hangzhou, 310000, China; College of Basic Medical Sciences, Zhejiang Chinese Medical University, Hangzhou, 310000, China; Academy of Chinese Medical Science, Zhejiang Chinese Medical University, Hangzhou, 310000, China
Jiangxue Han: Zhejiang Key Laboratory of Blood-Stasis-Toxin Syndrome, Zhejiang Chinese Medical University, Hangzhou, 310000, China; Zhejiang Engineering Research Center for “Preventive Treatment” Smart Health of Traditional Chinese Medicine, Zhejiang Chinese Medical University, Hangzhou, 310000, China; College of Basic Medical Sciences, Zhejiang Chinese Medical University, Hangzhou, 310000, China; Academy of Chinese Medical Science, Zhejiang Chinese Medical University, Hangzhou, 310000, China
Zhu Huang: Zhejiang Key Laboratory of Blood-Stasis-Toxin Syndrome, Zhejiang Chinese Medical University, Hangzhou, 310000, China; Zhejiang Engineering Research Center for “Preventive Treatment” Smart Health of Traditional Chinese Medicine, Zhejiang Chinese Medical University, Hangzhou, 310000, China; College of Basic Medical Sciences, Zhejiang Chinese Medical University, Hangzhou, 310000, China
Yahui Lou: Zhejiang Key Laboratory of Blood-Stasis-Toxin Syndrome, Zhejiang Chinese Medical University, Hangzhou, 310000, China; Zhejiang Engineering Research Center for “Preventive Treatment” Smart Health of Traditional Chinese Medicine, Zhejiang Chinese Medical University, Hangzhou, 310000, China; College of Basic Medical Sciences, Zhejiang Chinese Medical University, Hangzhou, 310000, China
Bingyue Zhang: Zhejiang Key Laboratory of Blood-Stasis-Toxin Syndrome, Zhejiang Chinese Medical University, Hangzhou, 310000, China; Zhejiang Engineering Research Center for “Preventive Treatment” Smart Health of Traditional Chinese Medicine, Zhejiang Chinese Medical University, Hangzhou, 310000, China; College of Basic Medical Sciences, Zhejiang Chinese Medical University, Hangzhou, 310000, China
Yanjie Wang: Zhejiang Key Laboratory of Blood-Stasis-Toxin Syndrome, Zhejiang Chinese Medical University, Hangzhou, 310000, China; Zhejiang Engineering Research Center for “Preventive Treatment” Smart Health of Traditional Chinese Medicine, Zhejiang Chinese Medical University, Hangzhou, 310000, China; College of Basic Medical Sciences, Zhejiang Chinese Medical University, Hangzhou, 310000, China
Xiaoning Sun: Affiliated Hospital of Liaoning University of Traditional Chinese Medicine, Shenyang, 110032, China
Yan Zhang: Affiliated Hospital of Liaoning University of Traditional Chinese Medicine, Shenyang, 110032, China
Aisong Zhu: Zhejiang Key Laboratory of Blood-Stasis-Toxin Syndrome, Zhejiang Chinese Medical University, Hangzhou, 310000, China; Zhejiang Engineering Research Center for “Preventive Treatment” Smart Health of Traditional Chinese Medicine, Zhejiang Chinese Medical University, Hangzhou, 310000, China; College of Basic Medical Sciences, Zhejiang Chinese Medical University, Hangzhou, 310000, China; Corresponding author. College of Basic Medical Sciences, Zhejiang Chinese Medical University, Hangzhou, 310000, China.

Journal volume & issue: Vol. 14, no. 4
p. 100914

Abstract

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Recent trends suggest that Chinese herbal medicine formulas (CHM formulas) are promising treatments for complex diseases. To characterize the precise syndromes, precise diseases and precise targets of the precise targets between complex diseases and CHM formulas, we developed an artificial intelligence-based quantitative predictive algorithm (DeepTCM). DeepTCM has gone through multilevel model calibration and validation against a comprehensive set of herb and disease data so that it accurately captures the complex cellular signaling, molecular and theoretical levels of traditional Chinese medicine (TCM). As an example, our model simulated the optimal CHM formulas for the treatment of coronary heart disease (CHD) with depression, and through model sensitivity analysis, we calculated the balanced scoring of the formulas. Furthermore, we constructed a biological knowledge graph representing interactions by associating herb-target and gene-disease interactions. Finally, we experimentally confirmed the therapeutic effect and pharmacological mechanism of a novel model-predicted intervention in humans and mice. This novel multiscale model opened up a new avenue to combine “disease syndrome” and “macro micro” system modeling to facilitate translational research in CHM formulas.

Published in Journal of Pharmaceutical Analysis

ISSN: 2095-1779 (Print); 2214-0883 (Online)
Publisher: Elsevier
Country of publisher: China
LCC subjects: Medicine: Therapeutics. Pharmacology
Website: http://www.journals.elsevier.com/journal-of-pharmaceutical-analysis/

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