Translational Systems Pharmacology‐Based Predictive Assessment of Drug‐Induced Cardiomyopathy
- Office of Clinical Pharmacology, Center for Drug Evaluation and Research, US Food and Drug Administration Silver Spring Maryland USA
- Department of Biomedical Sciences University of North Dakota, School of Medicine &, Health Sciences Grand Forks North Dakota USA
- College of Pharmacy University of Michigan Ann Arbor Michigan USA
- School of Mechanical Engineering National Technical University of Athens Zografou Greece
Drug‐induced cardiomyopathy contributes to drug attrition. We compared two pipelines of predictive modeling: (1) applying elastic net (EN) to differentially expressed genes (DEGs) of drugs; (2) applying integer linear programming (ILP) to construct each drug's signaling pathway starting from its targets to downstream proteins, to transcription factors, and to its DEGs in human cardiomyocytes, and then subjecting the genes/proteins in the drugs' signaling networks to EN regression. We classified 31 drugs with availability of DEGs into 13 toxic and 18 nontoxic drugs based on a clinical cardiomyopathy incidence cutoff of 0.1%. The ILP‐augmented modeling increased prediction accuracy from 79% to 88% (sensitivity: 88%; specificity: 89%) under leave‐one‐out cross validation. The ILP‐constructed signaling networks of drugs were better predictors than DEGs. Per literature, the microRNAs that reportedly regulate expression of our six top predictors are of diagnostic value for natural heart failure or doxorubicin‐induced cardiomyopathy. This translational predictive modeling might uncover potential biomarkers.
- Research Organization:
- Oak Ridge Institute for Science and Education (ORISE), Oak Ridge, TN (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC), Biological and Environmental Research (BER). Biological Systems Science Division
- Grant/Contract Number:
- SC0014664
- OSTI ID:
- 1417211
- Alternate ID(s):
- OSTI ID: 1417212; OSTI ID: 1630015
- Journal Information:
- CPT: Pharmacometrics & Systems Pharmacology, Journal Name: CPT: Pharmacometrics & Systems Pharmacology Vol. 7 Journal Issue: 3; ISSN 2163-8306
- Publisher:
- Wiley Blackwell (John Wiley & Sons)Copyright Statement
- Country of Publication:
- United States
- Language:
- English
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