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In Briefings in bioinformatics ; h5-index 0.0

MOTIVATION : Adverse drug reaction (ADR) or drug side effect studies play a crucial role in drug discovery. Recently, with the rapid increase of both clinical and non-clinical data, machine learning methods have emerged as prominent tools to support analyzing and predicting ADRs. Nonetheless, there are still remaining challenges in ADR studies.

RESULTS : In this paper, we summarized ADR data sources and review ADR studies in three tasks: drug-ADR benchmark data creation, drug-ADR prediction and ADR mechanism analysis. We focused on machine learning methods used in each task and then compare performances of the methods on the drug-ADR prediction task. Finally, we discussed open problems for further ADR studies.

AVAILABILITY : Data and code are available at

Nguyen Duc Anh, Nguyen Canh Hao, Mamitsuka Hiroshi


ADR mechanism, ADR prediction, adverse drug reaction, machine learning methods