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Predicting cooperative drug effects through the quantitative cellular profiling of response to individual drugs.


ABSTRACT: 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.

SUBMITTER: Zhao J 

PROVIDER: S-EPMC3944117 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Predicting cooperative drug effects through the quantitative cellular profiling of response to individual drugs.

Zhao J J   Zhang X-S XS   Zhang S S  

CPT: pharmacometrics & systems pharmacology 20140226


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  ...[more]

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