Open AccessPredicting cooperative drug effects through the quantitative cellular profiling of response to individual drugs
Author(s) -
Zhao J,
Zhang XS,
Zhang S
Publication year - 2014
Publication title -
cpt: pharmacometrics and systems pharmacology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.53
H-Index - 37
ISSN - 2163-8306
DOI - 10.1038/psp.2013.79
Subject(s) - profiling (computer programming) , drug , drug response , computational biology , drug discovery , gene expression profiling , dna microarray , microarray analysis techniques , drug development , computer science , bioinformatics , biology , pharmacology , gene expression , gene , genetics , operating system
Quantitative prediction of cellular responses to drugs and drug combinations is a challenging and valuable topic in pharmaceutical research. In the past decade, microarray technology has become a routine tool for monitoring genome‐wide expression changes and has been widely adopted for exploring drug response in the pharmaceutical field. However, how to predict the synergistic effect of drug combinations using microarray data is a challenging task. In this article, we report a simple prediction framework based on the genome‐wide and quantitative profiling of cellular responses to individual drugs. By exploring the differential expression profiles, our correlation‐based strategy can reveal the synergistic effects of drug combinations. The comparison with gold‐standard experimental results demonstrates the strengths and weaknesses in relation to prediction based only on cellular response to individual drugs. Specifically, the prediction strategy may work for a drug combination whose individual drugs show related transcriptomic mechanisms but not for others. CPT Pharmacometrics Syst. Pharmacol . (2014) 3, e102; doi: 10.1038/psp.2013.79 ; published online 26 February 2014