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ORIGINAL RESEARCH article

Front. Pharmacol.

Sec. Ethnopharmacology

Volume 16 - 2025 | doi: 10.3389/fphar.2025.1698202

This article is part of the Research TopicArtificial Intelligence in Traditional Medicine Research and ApplicationView all 17 articles

SZBC-AI4TCM: A Comprehensive Web-Based Computing Platform for Traditional Chinese Medicine Research and Development

Provisionally accepted
Jidong  LangJidong Lang1Kaimin  GuoKaimin Guo1Jinna  YangJinna Yang1Pengcheng  YangPengcheng Yang1Yu  WeiYu Wei1Jingwen  HanJingwen Han1Shuang  ZhaoShuang Zhao1Zhihong  LiuZhihong Liu2Haowei  YiHaowei Yi2Xin  YanXin Yan2Binbin  ChenBinbin Chen1Cheng  WangCheng Wang1Jian  XuJian Xu1Jiawei  GeJiawei Ge1Wen  ZhangWen Zhang1Xuezhong  ZhouXuezhong Zhou3Jiansong  FangJiansong Fang4Jing  SuJing Su1Kaijing  YanKaijing Yan1Yunhui  HuYunhui Hu1*Wenjia  WangWenjia Wang1*
  • 1Tianjin Tasly Digital Intelligence Chinese Medicine Technology Co., Ltd., Tianjin, China
  • 2Wecomput Technology Co., Ltd., Beijing, China
  • 3Beijing Jiaotong University, Beijing, China
  • 4Guangzhou University of Chinese Medicine, Guangzhou, China

The final, formatted version of the article will be published soon.

In recent years, the increasing complexity and volume of data in traditional Chinese medicine (TCM) research have rendered the conventional experimental methods inadequate for modern TCM development. The analysis of intricate TCM data demands proficiency in multiple programming languages, artificial intelligence techniques, and bioinformatics, posing significant challenges for researchers lacking such expertise. Thus, there is an urgent need to develop user-friendly software tools that encompass various aspects of TCM data analysis. We developed a comprehensive web-based computing platform, SZBC-AI4TCM, a comprehensive web-based computing platform for Traditional Chinese Medicine (TCM) that embodies the "ShuZhiBenCao" (Digital Herbal) concept through artificial intelligence (AI), designed to accelerate TCM research and reduce costs by integrating advanced AI algorithms and bioinformatics tools. Leveraging machine learning, deep learning, and big data analytics, the platform enables end-to-end analysis, from TCM formulation and mechanism elucidation to drug screening. Featuring an intuitive visual interface and hardware–software acceleration, SZBC-AI4TCM allows researchers without computational backgrounds to conduct comprehensive and accurate analyses efficiently. By using the TCM research in Alzheimer's disease as an example, we showcase its functionalities, operational methods, and analytical capabilities. SZBC-AI4TCM not only provides robust computational support for TCM research but also significantly enhances efficiency and reduces costs. It offers novel approaches for studying complex TCM systems, thereby advancing the modernization of TCM. As interdisciplinary collaboration and cloud computing continue to evolve, SZBC-AI4TCM is poised to play a strong role in TCM research and foster its growth in addition to contributing to global health. SZBC-AI4TCM is publicly for access at https://ai.tasly.com/ui/#/frontend/login. https://ai.tasly.com/ui/#/frontend/home/navigator-board.

Keywords: Traditional Chinese Medicine, artificial intelligence, deep learning, bioinformatics, web-based computing platform, Alzheimer's disease

Received: 03 Sep 2025; Accepted: 21 Oct 2025.

Copyright: © 2025 Lang, Guo, Yang, Yang, Wei, Han, Zhao, Liu, Yi, Yan, Chen, Wang, Xu, Ge, Zhang, Zhou, Fang, Su, Yan, Hu 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:
Yunhui Hu, tsl-huyunhui@tasly.com
Wenjia Wang, tsl-wangwenjia@tasly.com

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.