Zhu Ting, Liu Bing, Chen Ning, Liu Yuchen, Wang Zixuan, Tian Xue
Pharmaceutical Engineering Technology Research Center, Harbin University of Commerce, Harbin, China.
National Antitumor Natural Drug Engineering Research Center of Ministry of Education of Harbin University of Commerce, Harbin, China.
Curr Top Med Chem. 2025 Apr 24. doi: 10.2174/0115680266373236250411060857.
As Artificial Intelligence (AI) technology rapidly advances, its application in pharmaceutical formulation design and Drug Delivery Systems (DDS) is expanding, revealing significant potential. AI technology has played a role in optimizing drug design, enhancing research and development efficiency, and improving the safety profiles of pharmaceutical products, thereby supporting the realization of personalized medicine. This article systematically examines the foundational applications and principles of AI in pharmaceutical formulation, while also evaluating its role in key areas such as drug development, manufacturing, quality control, and ADME/T (absorption, distribution, metabolism, excretion, and toxicity) prediction. In particular, AI can enhance prediction accuracy for drug solubility, stability, and bioavailability, while optimizing novel DDS through Machine Learning (ML) models, such as nanocarrier design and personalized drug release control. Furthermore, AI has been pivotal in advancing intelligent manufacturing technologies, including three-dimensional printing (3D printing) and continuous manufacturing. Finally, the article explores the opportunities and challenges presented by AI in drug development, regulation, and policymaking. Overall, AI's integration promises to revolutionize pharmaceutical development and regulatory practices.
随着人工智能（AI）技术的迅速发展，其在药物制剂设计和药物递送系统（DDS）中的应用正在不断拓展，展现出巨大的潜力。人工智能技术在优化药物设计、提高研发效率以及改善药品安全性方面发挥了作用，从而助力个性化医疗的实现。本文系统地探讨了人工智能在药物制剂中的基础应用和原理，同时评估了其在药物研发、生产、质量控制以及ADME/T（吸收、分布、代谢、排泄和毒性）预测等关键领域的作用。特别是，人工智能可以提高药物溶解度、稳定性和生物利用度的预测准确性，同时通过机器学习（ML）模型优化新型药物递送系统，如纳米载体设计和个性化药物释放控制。此外，人工智能在推进智能制造技术，包括三维打印（3D打印）和连续制造方面发挥了关键作用。最后，本文探讨了人工智能在药物研发、监管和政策制定方面带来的机遇和挑战。总体而言，人工智能的融入有望彻底改变药物研发和监管实践。
