Integration and Innovation of AIDD and CADD: Cutting-Edge Technologies and Future Trends in Accelerating Drug Development

Traditional new drug R & D is mired in problems like long cycles, high costs, and low success rates. The integration of AIDD and CADD offers a fresh approach to breaking the “ten - year and ten - billion - dollar curse”. AIDD, with advanced technologies like deep learning and GANs, has greatly improved the efficiency of target identification, drug screening, and optimization. CADD, wielding established molecular modeling and virtual screening methods, lends theoretical backing to drug design. By analyzing cases of AIDD and CADD in target identification, virtual screening, and multimodal model application, the paper shows their advantages in speeding up drug discovery. Results indicate that their integration optimizes the R & D process, reducing costs and timelines. It also explores future trends like multimodal data fusion, reinforcement learning, and AI model interpretability, presenting strategies for tackling challenges in data quality and interdisciplinary collaboration. This paper focuses on the integrative innovation between artificial intelligence-driven drug design (AIDD) and computer - assisted drug design (CADD), delving into their role in accelerating drug development and future trends. Tied to China's biopharmaceutical industry growth, the paper proposes national - strategy recommendations, stressing international cooperation and policy support. The integrative innovation of AIDD and CADD heralds new opportunities for advancing personalized and precision medicine.