Page 129 - 南京医科大学自然版
P. 129

第46卷第6期                           南京医科大学学报(自然科学版)
                  2026年6月                   Journal of Nanjing Medical University(Natural Sciences)    ·911  ·


               ·综     述·

                人工智能在药物递送中的应用



                丁 妍 ,李晓林 ,徐华娥           1*
                       1
                               2
                南京医科大学药学院药剂学系,江苏              南京 211166;南京医科大学第一附属医院老年消化科,江苏                   南京    210029
                1                                         2


               [摘   要] 人工智能(artificial intelligence,AI)正驱动现代药物递送系统向智能化与精准化范式变革。为应对传统研发中周
                期长、成本高及靶向性不足等挑战,文章系统综述了AI技术在整个药物递送链条中的赋能作用。通过解析机器学习和深度学
                习等AI技术在多种剂型(包括传统剂型、缓释系统、微球/微囊、纳米载体及3D打印制剂)开发中的应用实例,阐明了AI模型在
                预测药物释放行为、优化配方设计、智能识别制剂缺陷以及实现个性化给药等方面的显著优势。文章指出,尽管面临数据质
                量、模型可解释性等挑战,AI无疑已成为推动药物递送迈向智能响应与精准医学时代的核心驱动力,在医药研发变革领域展
                现出巨大潜力。
               [关键词] 人工智能;药物递送;机器学习;精准医疗;制剂优化
               [中图分类号] R319                     [文献标志码] A                       [文章编号] 1007⁃4368(2026)06⁃911⁃09
                doi:10.7655/NYDXBNSN260204


                Application of artificial intelligence in drug delivery

                         1
                                   2
                DING Yan ,LI Xiaolin ,XU Hua’e 1*
                Department of Pharmaceutics,School of Pharmacy,Nanjing Medical University,Nanjing 211116;Department of
                1                                                                                   2
                Geriatric Gastroenterology,the First Affiliated Hospital of Nanjing Medical University,Nanjing 210029,China

               [Abstract] Artificial intelligence(AI)is driving the paradigm shift of modern drug delivery systems towards intelligence and
                precision. To address the challenges of long cycles,high costs,and insufficient targeting in traditional research and development,this
                article systematically reviews the empowering role of AI technology throughout the entire drug delivery chain. By analyzing application
                examples of AI technologies such as machine learning and deep learning in the development of various dosage forms(including
                traditional dosage forms,sustained ⁃ release systems,microspheres/microcapsules,nanocarriers,and 3D ⁃ printed formulations),the
                article elucidates the significant advantages of AI models in predicting drug release behavior,optimizing formulation design,
                intelligently identifying formulation defects,and achieving personalized drug delivery. The article points out that despite challenges
                such as data quality and model interpretability,AI has undoubtedly become the core driving force propelling drug delivery towards the
                era of intelligent response and precision medicine,demonstrating immense potential in the field of pharmaceutical research and
                development transformation.
               [Key words] artificial intelligence;drug delivery;machine learning;precision medicine;formulation optimization
                                                                          [J Nanjing Med Univ,2026,46(06):911⁃918,934]





                    近年来,药物递送系统(drug delivery system,              量药物送达病灶”,从而显著提升疗效、减少不良反
                DDS)发展迅速,其通过精准靶向、智能控释和跨越                          应并改善患者依从性。但 DDS 仍面临着递药效率
                生物屏障等核心技术,实现了“在正确的时间将适                            低、靶向精准性不足、研发周期长和成本高等严峻挑

                                                                  战。作为连接活性药物成分(active pharmaceutical
               [基金项目] 国家自然科学基金(82373105);白求恩·医学                   ingredient,API)与临床转化的核心桥梁,DDS 目前
                科学研究基金(2023⁃YJ⁃119⁃J⁃039)
                ∗                                                 面临的这些问题亟待解决。人工智能(artificial
                通信作者(Corresponding author),E⁃mail:xuhuae@njmu.edu.
                cn(ORCID:0000⁃0001⁃9124⁃303X)                     intelligence,AI)的有机融入,正在为该领域的突破
   124   125   126   127   128   129   130   131   132   133   134