Integrating TCM Theory with AI: A BP-GA Hybrid Framework for Precision Optimization of Multi-Herb Formulations in Gastric Cancer Treatment

Issue  JCB, Volume 30, Number 3, 2025  Article 

Yujia Jing
School of Traditional Chinese Medicine and Food Engineering, Shanxi University of Traditional Chinese Medicine, Taiyuan 030619, China
Mingyi Sun
Institute of Traditional Chinese Medicine, Shanxi Academy of Traditional Chinese Medicine, Taiyuan 030012, China
Han Wang
School of Traditional Chinese Medicine and Food Engineering, Shanxi University of Traditional Chinese Medicine, Taiyuan 030619, China
Ziqi Yao
Institute of Traditional Chinese Medicine, Shanxi Academy of Traditional Chinese Medicine, Taiyuan 030012, China
Yan Ni
Institute of Traditional Chinese Medicine, Shanxi Academy of Traditional Chinese Medicine, Taiyuan 030012, China

Abstract:

Gastric cancer remains a leading cause of global cancer mortality, necessitating innovative therapeutic strategies that balance efficacy with safety. This study presents a novel hybrid artificial intelligence framework integrating backpropagation neural networks (BPNN) and genetic algorithms (GA) to optimize dosing strategies for a multi-herb Traditional Chinese Medicine (TCM) prescription in gastric cancer treatment. Our approach uniquely addresses three critical challenges: (1) the nonlinear pharmacodynamics of herbal combinations, (2) the quantitative operationalization of classical TCM theory (Jun-Chen-Zuo-Shi principles), and (3) the reconciliation of empirical knowledge with precision medicine requirements. Through Plackett-Burman screening and orthogonal experimental designs, we identified Actinidia arguta (28.7% contribution, p=0.003), Scutellaria barbata (22.4%, p=0.007), and Strychnos nux-vomica (18.9%, p=0.012) as key bioactive components, demonstrating significant synergistic interactions (?-inhibition >15%, p<0.001). The BP-GA model achieved superior predictive accuracy (R²=0.941) compared to conventional methods, enabling precise dosage optimization via Pareto front analysis (63g Actinidia arguta, 68g Scutellaria barbata, 4.8g Strychnos nux-vomica). In a phase III randomized controlled trial (n=216), the optimized formulation significantly extended median survival by 4.3 months (HR=0.62, p<0.001), improved response rates (82.4% vs 68.7%, p<0.05), and reduced gastrointestinal toxicity by 35.7% (p<0.05). These results validate our computational approach in bridging TCM theory with clinical outcomes while establishing a new paradigm for evidence-based herbal medicine development. The framework's adaptability suggests broad applicability across integrative oncology and complex polypharmacy optimization.

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