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      SynergyFinder: a web application for analyzing drug combination dose–response matrix data

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          Abstract

          Summary

          Rational design of drug combinations has become a promising strategy to tackle the drug sensitivity and resistance problem in cancer treatment. To systematically evaluate the pre-clinical significance of pairwise drug combinations, functional screening assays that probe combination effects in a dose–response matrix assay are commonly used. To facilitate the analysis of such drug combination experiments, we implemented a web application that uses key functions of R-package SynergyFinder, and provides not only the flexibility of using multiple synergy scoring models, but also a user-friendly interface for visualizing the drug combination landscapes in an interactive manner.

          Availability and Implementation

          The SynergyFinder web application is freely accessible at https://synergyfinder.fimm.fi; The R-package and its source-code are freely available at http://bioconductor.org/packages/release/bioc/html/synergyfinder.html.

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          Most cited references4

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          The problem of synergism and antagonism of combined drugs.

          S. Loewe (1953)
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            What is synergy?

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              Targeting the cancer kinome through polypharmacology.

              Kinase inhibitors are the largest class of new cancer drugs. However, it is already apparent that most tumours can escape from the inhibition of any single kinase. If it is necessary to inhibit multiple kinases, how do we choose which ones? In this Opinion article, we discuss some of the strategies that are currently being used to identify new therapeutic combinations of kinase targets.
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                Author and article information

                Contributors
                Role: Associate Editor
                Journal
                9808944
                20940
                Bioinformatics
                Bioinformatics
                Bioinformatics (Oxford, England)
                1367-4803
                1367-4811
                8 June 2017
                01 August 2017
                13 August 2017
                : 33
                : 15
                : 2413-2415
                Affiliations
                [1 ]Institute for Molecular Medicine Finland (FIMM), University of Helsinki, FI-00290 Helsinki, Finland
                [2 ]Department of Mathematics and Statistics, University of Turku, Quantum, FI-20014 Turku, Finland
                Author notes
                [* ]To whom correspondence should be addressed. jing.tang@ 123456helsinki.fi
                Article
                EMS73059
                10.1093/bioinformatics/btx162
                5554616
                28379339
                10bb3dfc-1f6f-47db-b4e7-75ecd361224a

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@ 123456oup.com

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                Bioinformatics & Computational biology
                Bioinformatics & Computational biology

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