REVIEW article
Front. Mol. Biosci.
Sec. Molecular Diagnostics and Therapeutics
This article is part of the Research TopicPrecision Medicine: Innovations in Molecular Diagnosis and TreatmentView all articles
Bridging Ancient Wisdom and Modern Technology: An AI and Multi-Omics Framework for Three Causes Tailored Treatment in Personalized Medicine
Provisionally accepted
- 1First Affiliated Hospital of Henan University of Traditional Chinese Medicine, Zhengzhou, China
- 2The First Clinical Medical School, Henan University of Chinese Medicine, Zhengzhou, China
- 3Faculty of Chinese Medicine, Macau University of Science and Technology, Taipa, Macao, SAR China
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The 'one-size-fits-all' therapeutic model is inadequate to address individual patient variability, 18 creating an urgent need for an integrative framework for precision medicine. The 'Three Causes 19 Tailored Treatment' (TCTT) principle from traditional Chinese medicine offers a time-tested, holistic 20 blueprint that simultaneously considers the individual, temporal, and environmental dimensions of 21 health. Here, we argue that the synergy of artificial intelligence (AI) and multi-omics technologies is 22 the key to transforming this ancient wisdom into a modern, quantitative clinical paradigm. We 23 demonstrate how multi-omics data provides the foundational layers to quantify the TCTT principle— 24 for instance, using integrated omics (e.g., genomics, proteomics, microbiome) to establish the 25 individual's molecular baseline ("Who"); chronomics to capture temporal fluxes ("When"); and the 26 exposome to decipher the internalized environmental imprint ("Where")—while AI-powered 27 multimodal integration models their complex interactions. By synthesizing evidence across the 28 disease continuum, this review provides a translational roadmap for building dynamic clinical 29 decision-support systems, thereby charting a course toward truly personalized, time-sensitive, and 30 context-aware healthcare.
Keywords: artificial intelligence, multi-omics, Three Causes Tailored Treatment, personalized medicine, Integrative Medicine
Received: 25 Oct 2025; Accepted: 02 Dec 2025.
Copyright: © 2025 Diao, Hao, Wang, Zhang and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Qi Zhang
Zulong Wang
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