Accurate early warning and effective intervention for tumor occurrence are crucial for reducing tumor incidence. In the era of artificial intelligence, how can traditional Chinese medicine, with its unique "preventive treatment" philosophy and extensive practical experience, better contribute to cancer prevention and treatment? Professor Li Shao, director of the Beijing Institute for Integrated Traditional Chinese and Western Medicine at Tsinghua University and an academician of the European Academy of Sciences and Arts, has led a team in over 20 years of research to develop a new method for cancer prevention and treatment called AI-TWM, based on artificial intelligence, which has demonstrated excellent application results in the early prevention and treatment of gastric cancer.

This significant achievement in cancer prevention methodology provides new perspectives for research on early cancer prevention and traditional medicine, and was recently published in the prestigious journal 'Cancer Discovery' under the American Association for Cancer Research.

The AI-TWM method for integrated traditional Chinese and Western medicine in cancer prevention and treatment. (Photo provided by the interviewee)

According to reports, the core of AI-TWM lies in utilizing a biologically network-based artificial intelligence algorithm to systematically uncover macro modal features related to cancer risk from both traditional Chinese and Western medicine, constructing an intelligent early warning model for cancer risk that integrates both fields. This method enables precise identification of high-risk populations for tumor occurrence. Additionally, through the team’s self-developed network pharmacology analysis method, the molecular networks of tumor occurrence and intervention mechanisms are systematically identified, and potential drugs from traditional Chinese medicine that can effectively inhibit tumor occurrence are uncovered.

“By integrating a series of independently developed high-precision predictive algorithms with clinical and experimental validation, we have achieved a panoramic analysis of the multi-level network correlations among traditional and Western medicine phenotypes, tissues, cells, molecules, and drugs. We constructed a molecular network navigation system for traditional Chinese and Western medicine, solving the long-standing difficulty of explaining the 'complexity' principle of traditional Chinese medicine caused by the intricate links between the complex components of herbal medicine and corresponding diseases,” said Li Shao.

He further explained that through this method, the team established an "Intelligent and Precise Prevention and Treatment System for Early Gastric Cancer" by collecting and analyzing over 500,000 clinical data cases of gastric inflammation transitioning to cancer, and through the analysis of multi-level biological networks, discovered risk warning features relevant to gastric cancer as well as indicators of "extremely early cellular changes in gastric cancer." Currently, this system has been promoted and applied in several high-incidence areas of gastric cancer in China and over 50 hospitals, assisting in the construction of national demonstration zones for comprehensive prevention and control of chronic diseases, making preventive treatment for tumors achievable.