Abstract: Synthetic biology integrates engineering principles with biology to design and reprogram biological systems for applications in health, energy, and the environment. Recent advances in artificial intelligence (AI), particularly deep learning, are revolutionizing medical synthetic biology by enabling intelligent component design, pathway optimization, disease diagnosis, and advanced therapeutics. This review highlights key breakthroughs, including AlphaFold-guided CAR-T optimization and AI-driven AAV capsid evolution that have transformed gene and cell therapy design. We discuss critical challenges—data quality, model interpretability, biosafety, and ethics—and outline future directions toward AI-enabled automation, multimodal modeling, and personalized medicine. The convergence of AI and synthetic biology marks a paradigm shift toward intelligent, data-driven precision medicine.