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 machine learning and deep learning, have transformed synthetic biology by enabling intelligent component design, pathway optimization, disease diagnosis, and drug discovery. This review highlights major breakthroughs in protein engineering, genome editing, microbial and cell therapies, and vaccine design, with emphasis on clinical translation. Key challenges—including data quality, model interpretability, biosafety, and ethics—are discussed alongside prospects for AI-driven automation, multimodal modeling, and personalized medicine. The convergence of AI and synthetic biology is accelerating precision and personalized medicine at an unprecedented pace.