title: Automatic filtering and substantiation of drug safety signals.
abstract: 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. First, the proposed framework investigates previous evidences on the drug-event association in the context of biomedical literature (signal filtering). Then, it 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 workflows for signal filtering and substantiation integrate modules for literature and database mining, in silico drug-target profiling, and analyses based on gene-disease networks and biological pathways. Application examples of these workflows carried out on selected cases of drug safety signals are discussed. The methodology and workflows presented offer a novel approach to explore the molecular mechanisms underlying adverse drug reactions.
authors.affiliation: Research Programme on Biomedical Informatics-GRIB, IMIM-Hospital del Mar Research Institute, DCEX, Universitat Pompeu Fabra, Barcelona, Spain.
authors.forename: Anna
authors.initials: A
authors.lastname: Bauer-Mehren
authors.forename: Erik M
authors.initials: EM
authors.lastname: van Mullingen
authors.forename: Paul
authors.initials: P
authors.lastname: Avillach
authors.forename: María Del Carmen
authors.initials: Mdel C
authors.lastname: Carrascosa
authors.forename: Ricard
authors.initials: R
authors.lastname: Garcia-Serna
authors.forename: Janet
authors.initials: J
authors.lastname: Piñero
authors.forename: Bharat
authors.initials: B
authors.lastname: Singh
authors.forename: Pedro
authors.initials: P
authors.lastname: Lopes
authors.forename: José L
authors.initials: JL
authors.lastname: Oliveira
authors.forename: Gayo
authors.initials: G
authors.lastname: Diallo
authors.forename: Ernst
authors.initials: E
authors.lastname: Ahlberg Helgee
authors.forename: Scott
authors.initials: S
authors.lastname: Boyer
authors.forename: Jordi
authors.initials: J
authors.lastname: Mestres
authors.forename: Ferran
authors.initials: F
authors.lastname: Sanz
authors.forename: Jan A
authors.initials: JA
authors.lastname: Kors
authors.forename: Laura I
authors.initials: LI
authors.lastname: Furlong
mesh_terms: D003198:Computer Simulation; D003628:Database Management Systems; D016208:Databases, Factual; D004282:Documentation / Q000379:methods*; D064420:Drug-Related Side Effects and Adverse Reactions / Q000145:classification* / Q000453:epidemiology*; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods*; D008954:Models, Biological; D012042:Registries