药物分子多晶型预测技术发展与展望  

Development and prospects of predicting drug polymorphs technology

作　　者：郭妹[1] 丁文星 彭勃[1] 刘劲风 苏沂菲 朱彬[1] 任国宾[1] GUO Mei;DING Wen-xing;PENG Bo;LIU Jin-feng;SU Yi-fei;ZHU Bin;REN Guo-bin(State Key Laboratory of Bioreactor Engineering,Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism,Shanghai Key Laboratory of New Drug Design,Engineering Research Centre of Pharmaceutical Process Chemistry,Laboratory of Pharmaceutical Crystal Engineering&Technology,East China University of Science and Technology,Shanghai 200237,China)

机构地区：[1]华东理工大学,生物反应器工程国家重点实验室,上海市新药设计重点实验室,上海市细胞代谢光遗传学技术前沿科学研究基地,制药工程与过程化学教育部工程研究中心,药物晶体工程技术研究实验室,上海200237

出　　处：《药学学报》2024年第1期76-83,共8页Acta Pharmaceutica Sinica

基　　金：国家自然科学基金资助项目(22078094,21776073,21908055);中国博士后科学基金资助项目(2021M701188,2019M661410);苏州市社会发展科技创新资助项目(2022SS27)。

摘　　要：大部分的化学药物都存在多晶型现象。药物多晶型的理化性质差异直接影响固态药物制剂产品的稳定性、有效性和安全性,因此药物多晶型的研究是药物化学、制造和控制的重要组成部分,也是影响高端原料药及制剂质量的关键因素。多晶型预测技术可以高效指导试错性实验的筛选,降低传统筛选实验遗漏稳定晶型带来的风险。药物分子多晶型预测技术正在不断发展进步,最初是基于量子力学和计算化学等理论计算,后有应用人工智能的机器学习关键技术,以及联合理论计算和机器学习两者优势共同预测晶体结构。目前,准确预测药物分子晶型依旧具有挑战性,但有望借鉴并综合现有技术,开发更加精确且高效的预测晶型技术。Most chemical medicines have polymorphs.The difference of medicine polymorphs in physicochemical properties directly affects the stability,efficacy,and safety of solid medicine products.Polymorphs is incomparably important to pharmaceutical chemistry,manufacturing,and control.Meantime polymorphs is a key factor for the quality of high-end drug and formulations.Polymorph prediction technology can effectively guide screening of trial experiments,and reduce the risk of missing stable crystal form in the traditional experiment.Polymorph prediction technology was firstly based on theoretical calculations such as quantum mechanics and computational chemistry,and then was developed by the key technology of machine learning using the artificial intelligence.Nowadays,the popular trend is to combine the advantages of theoretical calculation and machine learning to jointly predict crystal structure.Recently,predicting medicine polymorphs has still been a challenging problem.It is expected to learn from and integrate existing technologies to predict medicine polymorphs more accurately and efficiently.

关 键 词：药物多晶型 晶体结构预测 机器学习 计算化学 

分 类 号：R917[医药卫生—药物分析学]