Adverse drug reactions (ADRs) are the leading factors of drug attrition in drug development
and post-market drug withdrawal. The identification of potential ADRs can help prevent the
failure of drug discovery and improve development efficiency. Furthermore, elucidating possible
ADRs for known drugs can help better understand the mechanism of drug actions and even find new
indications of old drugs. Unfortunately, only the ADRs of some well-studied drugs are available and
our knowledge about ADRs of available drugs is far from complete. Recently, with more structural
and omics data available, some computational approaches have been developed for predicting drug
ADRs. In this review, we present a survey on the recent progresses on computational methodologies
that have been developed for ADR prediction based on various kinds of data, and some ADR related
resources are also introduced.
Keywords: Adverse drug reaction, Side effect, In silico prediction, Molecular structure, Molecular circuit, Heterogeneous network.
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