Drug Safety

, Volume 39, Issue 7, pp 697–707 | Cite as

Linking MedDRA®-Coded Clinical Phenotypes to Biological Mechanisms by the Ontology of Adverse Events: A Pilot Study on Tyrosine Kinase Inhibitors

  • Sirarat Sarntivijai
  • Shelley Zhang
  • Desikan G. Jagannathan
  • Shadia Zaman
  • Keith K. Burkhart
  • Gilbert S. Omenn
  • Yongqun He
  • Brian D. Athey
  • Darrell R. Abernethy
Original Research Article



A translational bioinformatics challenge exists in connecting population and individual clinical phenotypes in various formats to biological mechanisms. The Medical Dictionary for Regulatory Activities (MedDRA®) is the default dictionary for adverse event (AE) reporting in the US Food and Drug Administration Adverse Event Reporting System (FAERS). The ontology of adverse events (OAE) represents AEs as pathological processes occurring after drug exposures.


The aim of this work was to establish a semantic framework to link biological mechanisms to phenotypes of AEs by combining OAE with MedDRA® in FAERS data analysis. We investigated the AEs associated with tyrosine kinase inhibitors (TKIs) and monoclonal antibodies (mAbs) targeting tyrosine kinases. The five selected TKIs/mAbs (i.e., dasatinib, imatinib, lapatinib, cetuximab, and trastuzumab) are known to induce impaired ventricular function (non-QT) cardiotoxicity.


Statistical analysis of FAERS data identified 1053 distinct MedDRA® terms significantly associated with TKIs/mAbs, where 884 did not have corresponding OAE terms. We manually annotated these terms, added them to OAE by the standard OAE development strategy, and mapped them to MedDRA®. The data integration to provide insights into molecular mechanisms of drug-associated AEs was performed by including linkages in OAE for all related AE terms to MedDRA® and the existing ontologies, including the human phenotype ontology (HP), Uber anatomy ontology (UBERON), and gene ontology (GO). Sixteen AEs were shared by all five TKIs/mAbs, and each of 17 cardiotoxicity AEs was associated with at least one TKI/mAb. As an example, we analyzed “cardiac failure” using the relations established in OAE with other ontologies and demonstrated that one of the biological processes associated with cardiac failure maps to the genes associated with heart contraction.


By expanding the existing OAE ontological design, our TKI use case demonstrated that the combination of OAE and MedDRA® provides a semantic framework to link clinical phenotypes of adverse drug events to biological mechanisms.


Lapatinib Dasatinib Proportional Reporting Ratio Human Phenotype Mammalian Phenotype 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The authors thank Zuoshuang Xiang for his programming assistance in building OAE.

Compliance with Ethical Standards


This work was supported by the Oak Ridge Institute for Science and Education (ORISE) (Sirarat Sarntivijai), the Undergraduate Research Opportunity Program at the University of Michigan (Shelley Zhang, Desikan Jagannathan, Yongqun He), the Food and Drug Administration (FDA) Commissioner’s Fellowship Program (Shadia Zaman), National Institute of Environmental Health Sciences (NIEHS) Grant Number P30ES017885-01A1 (Gilbert Omenn), National Institutes of Health (NIH) Grant Numbers U54 DA021529 and UL1 TR000433-09 (Brian Athey), and National Institute of Allergy and Infectious Disease (NIAID) Grant Number R01 AI081062 (Yongqun He).

Conflict of interest

Sirarat Sarntivijai, Shelley Zhang, Desikan Jagannathan, Shadia Zaman, Keith Burkhart, Gilbert Omenn, Yongqun He, Brian Athey, and Darrell Abernethy have no conflicts of interest that are directly relevant to the content of this study.

Supplementary material

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Copyright information

© Springer International Publishing Switzerland (Outside the USA) 2016

Authors and Affiliations

  • Sirarat Sarntivijai
    • 1
    • 6
  • Shelley Zhang
    • 2
  • Desikan G. Jagannathan
    • 3
  • Shadia Zaman
    • 1
  • Keith K. Burkhart
    • 1
  • Gilbert S. Omenn
    • 5
    • 6
    • 7
  • Yongqun He
    • 4
    • 6
    • 8
  • Brian D. Athey
    • 6
    • 7
    • 9
  • Darrell R. Abernethy
    • 1
  1. 1.Office of Clinical Pharmacology, Office of Translational ScienceCenter for Drug Evaluation and Research, Food and Drug AdministrationSilver SpringUSA
  2. 2.College of Literature, Science, and the ArtsUniversity of MichiganAnn ArborUSA
  3. 3.College of EngineeringUniversity of MichiganAnn ArborUSA
  4. 4.Unit of Laboratory Animal MedicineUniversity of MichiganAnn ArborUSA
  5. 5.Department of Internal Medicine and Human Genetics and School of Public HealthUniversity of MichiganAnn ArborUSA
  6. 6.Center for Computational Medicine and BioinformaticsUniversity of MichiganAnn ArborUSA
  7. 7.Department of Computational Medicine and BioinformaticsUniversity of MichiganAnn ArborUSA
  8. 8.Department of Microbiology and ImmunologyUniversity of MichiganAnn ArborUSA
  9. 9.Psychiatry DepartmentUniversity of MichiganAnn ArborUSA

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