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Title: Systematic drug safety evaluation based on public genomic expression (Connectivity Map) data: Myocardial and infectious adverse reactions as application cases

Abstract

Adverse drug reaction (ADR) is of great importance to both regulatory agencies and the pharmaceutical industry. Various techniques, such as quantitative structure–activity relationship (QSAR) and animal toxicology, are widely used to identify potential risks during the preclinical stage of drug development. Despite these efforts, drugs with safety liabilities can still pass through safety checkpoints and enter the market. This situation raises the concern that conventional chemical structure analysis and phenotypic screening are not sufficient to avoid all clinical adverse events. Genomic expression data following in vitro drug treatments characterize drug actions and thus have become widely used in drug repositioning. In the present study, we explored prediction of ADRs based on the drug-induced gene-expression profiles from cultured human cells in the Connectivity Map (CMap) database. The results showed that drugs inducing comparable ADRs generally lead to similar CMap expression profiles. Based on such ADR-gene expression association, we established prediction models for various ADRs, including severe myocardial and infectious events. Drugs with FDA boxed warnings of safety liability were effectively identified. We therefore suggest that drug-induced gene expression change, in combination with effective computational methods, may provide a new dimension of information to facilitate systematic drug safety evaluation. - Highlights: • Drugsmore » causing common toxicity lead to similar in vitro gene expression changes. • We built a model to predict drug toxicity with drug-specific expression profiles. • Drugs with FDA black box warnings were effectively identified by our model. • In vitro assay can detect severe toxicity in the early stage of drug development.« less

Authors:
 [1];  [2];  [1]; ;  [3];  [1]
  1. Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Shanghai Jiao Tong University, Shanghai (China)
  2. Japan National Institute of Occupational Safety and Health, Kawasaki (Japan)
  3. Department of Pharmaceutical Sciences, College of Pharmacy, University of South Florida, Tampa, FL (United States)
Publication Date:
OSTI Identifier:
22458471
Resource Type:
Journal Article
Resource Relation:
Journal Name: Biochemical and Biophysical Research Communications; Journal Volume: 457; Journal Issue: 3; Other Information: Copyright (c) 2015 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; ANIMAL CELLS; COMPARATIVE EVALUATIONS; DRUGS; FORECASTING; GENES; HAZARDS; IN VITRO; INDUSTRY; LIABILITIES; SAFETY ANALYSIS; SCREENING; TOXICITY

Citation Formats

Wang, Kejian, E-mail: kejian.wang.bio@gmail.com, Weng, Zuquan, Sun, Liya, Sun, Jiazhi, Zhou, Shu-Feng, and He, Lin, E-mail: helin@Bio-X.com. Systematic drug safety evaluation based on public genomic expression (Connectivity Map) data: Myocardial and infectious adverse reactions as application cases. United States: N. p., 2015. Web. doi:10.1016/J.BBRC.2014.12.096.
Wang, Kejian, E-mail: kejian.wang.bio@gmail.com, Weng, Zuquan, Sun, Liya, Sun, Jiazhi, Zhou, Shu-Feng, & He, Lin, E-mail: helin@Bio-X.com. Systematic drug safety evaluation based on public genomic expression (Connectivity Map) data: Myocardial and infectious adverse reactions as application cases. United States. doi:10.1016/J.BBRC.2014.12.096.
Wang, Kejian, E-mail: kejian.wang.bio@gmail.com, Weng, Zuquan, Sun, Liya, Sun, Jiazhi, Zhou, Shu-Feng, and He, Lin, E-mail: helin@Bio-X.com. Fri . "Systematic drug safety evaluation based on public genomic expression (Connectivity Map) data: Myocardial and infectious adverse reactions as application cases". United States. doi:10.1016/J.BBRC.2014.12.096.
@article{osti_22458471,
title = {Systematic drug safety evaluation based on public genomic expression (Connectivity Map) data: Myocardial and infectious adverse reactions as application cases},
author = {Wang, Kejian, E-mail: kejian.wang.bio@gmail.com and Weng, Zuquan and Sun, Liya and Sun, Jiazhi and Zhou, Shu-Feng and He, Lin, E-mail: helin@Bio-X.com},
abstractNote = {Adverse drug reaction (ADR) is of great importance to both regulatory agencies and the pharmaceutical industry. Various techniques, such as quantitative structure–activity relationship (QSAR) and animal toxicology, are widely used to identify potential risks during the preclinical stage of drug development. Despite these efforts, drugs with safety liabilities can still pass through safety checkpoints and enter the market. This situation raises the concern that conventional chemical structure analysis and phenotypic screening are not sufficient to avoid all clinical adverse events. Genomic expression data following in vitro drug treatments characterize drug actions and thus have become widely used in drug repositioning. In the present study, we explored prediction of ADRs based on the drug-induced gene-expression profiles from cultured human cells in the Connectivity Map (CMap) database. The results showed that drugs inducing comparable ADRs generally lead to similar CMap expression profiles. Based on such ADR-gene expression association, we established prediction models for various ADRs, including severe myocardial and infectious events. Drugs with FDA boxed warnings of safety liability were effectively identified. We therefore suggest that drug-induced gene expression change, in combination with effective computational methods, may provide a new dimension of information to facilitate systematic drug safety evaluation. - Highlights: • Drugs causing common toxicity lead to similar in vitro gene expression changes. • We built a model to predict drug toxicity with drug-specific expression profiles. • Drugs with FDA black box warnings were effectively identified by our model. • In vitro assay can detect severe toxicity in the early stage of drug development.},
doi = {10.1016/J.BBRC.2014.12.096},
journal = {Biochemical and Biophysical Research Communications},
number = 3,
volume = 457,
place = {United States},
year = {Fri Feb 13 00:00:00 EST 2015},
month = {Fri Feb 13 00:00:00 EST 2015}
}