Abstract
Traditional Chinese Medicine (TCM) has played a vital role in public health throughout history, particularly evidenced during the COVID-19 pandemic, where it demonstrated both accessibility and clinical efficacy. However, TCM faces critical challenges, including unsustainable medicinal resources, ambiguous multi-target mechanisms, and a lack of standardized clinical evaluation systems. Addressing these issues requires interdisciplinary integration, particularly between synthetic biology and artificial intelligence (AI). Synthetic biology offers solutions to resource scarcity and production standardization by enabling the sustainable biosynthesis of active compounds. Meanwhile, AI enhances TCM research through bioinformatics-driven compound prediction, machine learning-assisted quality control, and network pharmacology-based mechanism elucidation. AI also improves diagnostic reproducibility, aligning with synthetic biology's precision-driven framework. Together, these technologies facilitate the transformation of TCM from an experience-based practice into a standardized, evidence-based public health intervention. This review highlights the synergistic potential of AI and synthetic biology in overcoming TCM's modernization barriers. By leveraging AI for data-driven drug discovery and synthetic biology for scalable production, TCM can achieve sustainable development while retaining its therapeutic value. Future efforts should focus on enhancing AI interpretability, expanding biological databases, and optimizing cross-disciplinary collaboration to fully realize this integration.