Development and validation of a general appoach to predict and quantify the synergism of anti-cancer drugs using experimental design and artificial neural networks

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14310%2F13%3A00068012" target="_blank" >RIV/00216224:14310/13:00068012 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1016/j.talanta.2013.04.031" target="_blank" >http://dx.doi.org/10.1016/j.talanta.2013.04.031</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.talanta.2013.04.031" target="_blank" >10.1016/j.talanta.2013.04.031</a>

Result language

angličtina

Original language name

Development and validation of a general appoach to predict and quantify the synergism of anti-cancer drugs using experimental design and artificial neural networks

Original language description

The combination of two or more drugs using multidrug mixtures is a trend in the treatment of cancer. The goal is to search for a synergistic effect and thereby reduce the required dose and inhibit the development of resistance. An advanced model-free approach for data exploration and analysis, based on artificial neural networks (ANN) and experimental design is proposed to predict and quantify the synergism of drugs. The proposed method non-linearly correlates the concentrations of drugs with the cytotoxicity of the mixture, providing the possibility of choosing the optimal drug combination that gives the maximum synergism. The use of ANN allows for the prediction of the cytotoxicity of each combination of drugs in the chosen concentration interval. The method was validated by preparing and experimentally testing the combinations with the predicted highest synergistic effect. In all cases, the data predicted by the network were experimentally confirmed.

Czech name

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Czech description

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Type

J_x - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

CEP classification

CB - Analytical chemistry, separation

OECD FORD branch

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Project

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Continuities

Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year

2013

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Talanta

ISSN

0039-9140

e-ISSN

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Volume of the periodical

115

Issue of the periodical within the volume

2013

Country of publishing house

NL - THE KINGDOM OF THE NETHERLANDS

Number of pages

10

Pages from-to

84-93

UT code for WoS article

000328095600012

EID of the result in the Scopus database

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