Wang Nannan, Sun Huimin, Dong Jie, Ouyang Defang
State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences (ICMS), University of Macau, Macau, China.
National Institute for Food and Drug Control, No. 2, Tiantan Xili Road, Beijing, 100050, China.
Int J Pharm. 2021 Sep 25;607:120962. doi: 10.1016/j.ijpharm.2021.120962. Epub 2021 Jul 31.
Drug-excipient compatibility study is the essential basis for excipient selection at the pre-formulation stage. According to the pharmaceutical Quality by Design (QbD) principles, a comprehensive understanding of the ingredients' physicochemical properties and a theoretical evaluation of the interaction risk between the drugs and excipients are required for conducting rational compatibility experimental design. Currently, there is an urgent need to establish an artificial intelligence system for researchers to easily get through the problem because it is very inconvenient and hard to utilize those drug-excipient incompatibility data scattered in scientific literature. Here, we designed a knowledge-driven expert system named PharmDE for drug-excipient incompatibility risk evaluation. PharmDE firstly developed an information-rich database to store incompatibility data, covering 532 data items from 228 selected articles. Then, 60 drug-excipient interaction rules were created based on our knowledge and formulation research experiences. Finally, the expert system was developed by organically integrating the database searching and rule-based incompatibility risk prediction, which resulted in four main functionalities: basic search of incompatibility database, data matching by similarity search, drug incompatibility risk evaluation, and formulation incompatibility risk evaluation. PharmDE is expected to be a useful tool for drug-excipient compatibility study and accelerate drug formulation design. It is now freely available at https://pharmde.computpharm.org.
药物-辅料相容性研究是制剂研发前期辅料选择的重要依据。根据药品质量源于设计(QbD)原则,进行合理的相容性实验设计需要全面了解各成分的理化性质,并对药物与辅料之间的相互作用风险进行理论评估。目前,迫切需要建立一个人工智能系统,以便研究人员能够轻松解决这个问题,因为利用分散在科学文献中的那些药物-辅料不相容性数据非常不方便且困难。在此,我们设计了一个名为PharmDE的知识驱动型专家系统,用于药物-辅料不相容性风险评估。PharmDE首先开发了一个信息丰富的数据库来存储不相容性数据,涵盖从228篇选定文章中提取的532个数据项。然后,基于我们的知识和制剂研究经验创建了60条药物-辅料相互作用规则。最后,通过有机整合数据库搜索和基于规则的不相容性风险预测开发了该专家系统,其具有四个主要功能:不相容性数据库基本搜索、相似性搜索数据匹配、药物不相容性风险评估和制剂不相容性风险评估。预计PharmDE将成为药物-辅料相容性研究的有用工具,并加速药物制剂设计。目前可在https://pharmde.computpharm.org免费获取。