Work

Characterizing drug-related adverse events by joint analysis of biomedical and genomic data: A case study of drug-induced pulmonary fibrosis.

Year: 2018

Type: article

Abstract: Spontaneous reporting systems such as the FDA's adverse event reporting system (FAERS) present a great resource to mine for and analyze real-world medication usage. Our study is based on a central premise that FAERS captures unsuspected drug-related adverse events (AEs). Since drug-related AEs result for several reasons, no single approach will be able to predict the entire gamut of AEs. A fundamental premise of systems biology is that a full understanding of a biological process or phenotype (e.g., drug-related AE) requires that all the individual elements be studied in conjunction with one another. We therefore hypothesize that integrative analysis of FAERS-based drug-related AEs with the transcriptional signatures from disease models and drug treatments can lead to the generation of unbiased hypotheses for drug-induced AE-modulating mechanisms of action as well as drug combinations that may target those mechanisms. We test this hypothesis using drug-induced pulmonary fibrosis (DIPF) as a proof-of-concept study.

Source: Europe PMC (PubMed Central)

Authors: Alex Jiang, Anil G Jegga

Institutions: Cincinnati Children's Hospital Medical Center, University of Cincinnati

Language: English

Topic: Pharmacovigilance and Adverse Drug Reactions

Subfield: Toxicology

Field: Pharmacology, Toxicology and Pharmaceutics

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: green

Funder: National Institutes of Health

Award: Discovery and characterization of candidate therapeutics for drug-induced pulmonary disease