【摘要】 药物相互作用诱发的不良反应严重威胁患者的生命健康并导致巨大的经济损失,随着联用药物数目的增加,不良反应发生率显著上升采用传统方法评估联合用药风险效率低、成本高,而生物信息学研究方法可采用低成本和高通量的方式对海量生物学和医学大数据进行分析和挖掘,获取与药物不良反应相关的有价值的信息。本文从文献挖掘、数据挖掘和生理药物代谢动力学模型等方面系统综述了利用药物生物信息学挖掘潜在药物相互作用的方法,并对联合用药风险研究的潜在研究方向进行展望更多还原

【Abstract】 Adverse drug reactions(ADRs) induced by drug-drug interactions have posed a serious threat to patients’ health and caused immense economic losses. With the increase in the number of combined drugs, the occurrence rate of side effects has surged. Since traditional methods for discovering drug interactions are infficient and costly, the biomedical informatics based methods are able to acquire valuable information about ADR by analyzing and mining from biomedical big data at a low cost and with high throughput. Methods of discovering potential drug interactions through literature mining, data mining and physiologically based pharmacokinetic models are systematically reviewed in this paper. Also,the prospect of potential research fields of drug conbination is outlined.更多还原