title: Integrating Multiple Evidence Sources to Predict Adverse Drug Reactions Based on a Systems Pharmacology Model.
abstract: Identifying potential adverse drug reactions (ADRs) is critically important for drug discovery and public health. Here we developed a multiple evidence fusion (MEF) method for the large-scale prediction of drug ADRs that can handle both approved drugs and novel molecules. MEF is based on the similarity reference by collaborative filtering, and integrates multiple similarity measures from various data types, taking advantage of the complementarity in the data. We used MEF to integrate drug-related and ADR-related data from multiple levels, including the network structural data formed by known drug-ADR relationships for predicting likely unknown ADRs. On cross-validation, it obtains high sensitivity and specificity, substantially outperforming existing methods that utilize single or a few data types. We validated our prediction by their overlap with drug-ADR associations that are known in databases. The proposed computational method could be used for complementary hypothesis generation and rapid analysis of potential drug-ADR interactions.
authors.affiliation: School of Pharmaceutical Sciences, Central South University Changsha, P.R. China.
authors.forename: D-S
authors.initials: DS
authors.lastname: Cao
authors.affiliation: School of Mathematics and Statistics, Central South University Changsha, P.R. China.
authors.forename: N
authors.initials: N
authors.lastname: Xiao
authors.affiliation: School of Pharmaceutical Sciences, Central South University Changsha, P.R. China.
authors.forename: Y-J
authors.initials: YJ
authors.lastname: Li
authors.affiliation: School of Pharmaceutical Sciences, Central South University Changsha, P.R. China.
authors.forename: W-B
authors.initials: WB
authors.lastname: Zeng
authors.affiliation: Research Center of Modernization of Traditional Chinese Medicines, Central South University Changsha, P.R. China.
authors.forename: Y-Z
authors.initials: YZ
authors.lastname: Liang
authors.affiliation: Institute for Advancing Translational Medicine in Bone & Joint Diseases, School of Chinese Medicine, Hong Kong Baptist University Hong Kong SAR, P.R. China.
authors.forename: A-P
authors.initials: AP
authors.lastname: Lu
authors.affiliation: School of Mathematics and Statistics, Central South University Changsha, P.R. China.
authors.forename: Q-S
authors.initials: QS
authors.lastname: Xu
authors.affiliation: School of Pharmaceutical Sciences, Central South University Changsha, P.R. China.
authors.forename: A F
authors.initials: AF
authors.lastname: Chen