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

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About: Development and validation of a general appoach to predict and quantify the synergism of anti-cancer drugs using experimental design and artificial neural networks Goto Sponge NotDistinct Permalink

An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

Attributes	Values
rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
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. 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. (en)
Title	Development and validation of a general appoach to predict and quantify the synergism of anti-cancer drugs using experimental design and artificial neural networks Development and validation of a general appoach to predict and quantify the synergism of anti-cancer drugs using experimental design and artificial neural networks (en)
skos:prefLabel	Development and validation of a general appoach to predict and quantify the synergism of anti-cancer drugs using experimental design and artificial neural networks Development and validation of a general appoach to predict and quantify the synergism of anti-cancer drugs using experimental design and artificial neural networks (en)
skos:notation	RIV/00216224:14310/13:00068012!RIV14-MSM-14310___
http://linked.open...avai/predkladatel	Přírodovědecká fakulta
http://linked.open...avai/riv/aktivita	Z
http://linked.open...avai/riv/aktivity	Z(MSM0021622411)
http://linked.open...iv/cisloPeriodika	2013
http://linked.open...vai/riv/dodaniDat	2014
http://linked.open...aciTvurceVysledku	Havel, Josef Amato, Filippo
http://linked.open.../riv/druhVysledku	J - Článek v odborném periodiku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Masarykova univerzita / Přírodovědecká fakulta
http://linked.open...dnocenehoVysledku	69063
http://linked.open...ai/riv/idVysledku	RIV/00216224:14310/13:00068012
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	synergism of drugs; artificial neural network; experimental design; cancer (en)
http://linked.open.../riv/klicoveSlovo	experimental design artificial neural network cancer synergism of drugs
http://linked.open...odStatuVydavatele	NL - Nizozemsko
http://linked.open...ontrolniKodProRIV	[D2E00612795A]
http://linked.open...i/riv/nazevZdroje	Talanta
http://linked.open...in/vavai/riv/obor	CB
http://linked.open...ichTvurcuVysledku	2 (xsd:int)
http://linked.open...cetTvurcuVysledku	8 (xsd:int)
http://linked.open...UplatneniVysledku	2013
http://linked.open...v/svazekPeriodika	115
http://linked.open...iv/tvurceVysledku	Amato, Filippo Havel, Josef Pivetta, Tiziana Isaia, Francesco Manca, Matteo Pani, Alessandra Perra, Daniela Trudu, Federica
http://linked.open...ain/vavai/riv/wos	000328095600012
http://linked.open...n/vavai/riv/zamer	Study and application of plasma chemical reactions in non-isothermic low temperature plasma and its interaction with solid surface
issn	0039-9140
number of pages	10 (xsd:int)
http://bibframe.org/vocab/doi	10.1016/j.talanta.2013.04.031
http://localhost/t...ganizacniJednotka	14310

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