公开(公告)号：US20240347139A1

公开(公告)日：2024-10-17

申请号：US18533616

申请日：2023-12-08

申请人： University of Electronic Science and Technology of China

发明人： Jiajing ZHU ,  Yongguo LIU ,  Zhi CHEN ,  Yun ZHANG ,  Qiaoqin LI ,  Xin LU

IPC分类号： G16C20/10 ,  G16C20/50

CPC分类号： G16C20/10 ,  G16C20/50

摘要： Disclosed are a method, an apparatus, and a device for predicting adverse drug-drug interactions, and a readable storage medium, and relates to the technical field of pharmaceutical research and development. An objective of the present application is to provide the method, apparatus, and device for predicting adverse drug-drug interactions, and the readable storage medium for solving the above problems. To achieve the above objective, a technical solution adopted by the present application is as follows: acquiring first information; constructing an adverse drug-drug interaction prediction model according to the first information; acquiring second information, where the second information is molecular structure information of two drugs to be predicted; and outputting predicted adverse drug-drug interactions with the second information as an input into the adverse drug-drug interaction prediction model.

公开(公告)号：US20240170104A1

公开(公告)日：2024-05-23

申请号：US18325572

申请日：2023-05-30

申请人： University of Electronic Science and Technology of China

发明人： Jiajing ZHU ,  Yongguo LIU ,  Yun ZHANG ,  Qiaoqin LI ,  Zhi CHEN

IPC分类号： G16C20/30 ,  G16C20/70

CPC分类号： G16C20/30 ,  G16C20/70

摘要： The present invention discloses the method and system for predicting adverse drug-drug interactions by recovering the multi-attribute information of drugs and the medium. The method includes: collecting adverse drug-drug interactions data and multi-attribute data of drugs; constructing the recovery model of multi-attribute absent feature of drugs; correcting the recovery model of multi-attribute absent feature of drugs by the cosine similarity regularization term, and solving the corrected recovery model to obtain the common features and unique features of multi-attribute information of drugs; obtaining the multi-attribute information of two drugs, calculating common features and unique features of their multi-attribute information as the inputs of the prediction model to predict their adverse drug-drug interactions. The present invention improves the accuracy of the prediction of the adverse drug-drug interactions, promotes the experimental study of the adverse drug-drug interactions, and ensures the safety of medication.