Send to

Choose Destination
AMIA Jt Summits Transl Sci Proc. 2018 May 18;2017:91-97. eCollection 2018.

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

Jiang A1,2, Jegga AG1,3,4.

Author information

Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA.
Comell University, Ithaca, New York, USA.
Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA.
Department of Computer Science, University of Cincinnati College of Engineering, Cincinnati, Ohio, USA.


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.


Supplemental Content

Full text links

Icon for PubMed Central
Loading ...
Support Center