Drug safety issues pose serious health threats to the population and constitute a major cause of mortality worldwide. Due to the prominent implications to both public health and the pharmaceutical industry, it is of great importance to unravel the molecular mechanisms by which an adverse drug reaction can be potentially elicited. These mechanisms can be investigated by placing the pharmaco-epidemiologically detected adverse drug reaction in an information-rich context and by exploiting all currently available biomedical knowledge to substantiate it. We present a computational framework for the biological annotation of potential adverse drug reactions. The proposed framework seeks to provide a biological explanation (signal substantiation) by exploring mechanistic connections that might explain why a drug produces a specific adverse reaction. The mechanistic connections include the activity of the drug, related compounds and drug metabolites on protein targets, the association of protein targets to clinical events, and the annotation of proteins (both protein targets and proteins associated with clinical events) to biological pathways. Hence, the substantiation workflow (ADR-S workflow) integrates modules for in silico drug-target profiling, and analyses based on gene-disease networks and biological pathways. The ADR-S workflow offers a novel approach to explore the molecular mechanisms underlying adverse drug reactions.

ADR substantiation

This work was supported by the European Commission [EU-ADR, ICT-215847], Innovative Medicines Initiative [eTOX,115002], the AGAUR, Instituto de Salud Carlos III FEDER (CP10/00524) and COMBIOMED grants. The Research Unit on Biomedical Informatics (GRIB) is a node of the Spanish National Institute of Bioinformatics (INB). The authors wish to thank the NLM® for making UMLS® and MesH® available free of charge.