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Drug cocktail selection for the treatment of Chagas disease : a multi-objective approach

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URI
http://hdl.handle.net/20.500.14066/2831
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Author(s)
Torres, Mateo; Cáceres Silva, Juan JoséCONACYT Authority; Jiménez, Rubén; Yubero Rodríguez, Víctor Andrés; Vega Gómez, María CelesteCONACYT Authority; Rolón, Miriam SoledadCONACYT Authority; Cernuzzi, Luca CarloCONACYT Authority; Barán, BenjamínCONACYT Authority; Burgos Edwards, Alberto JavierCONACYT Authority
Date of publishing
2017
Type of publication
info:eu-repo/semantics/article
Subject(s)
Multi-objective optimisation
Drug repurposing
Chagas Disease
Genetic Algorithms
 
Abstract
Chagas disease is a parasitic disease, endemic in South America. As of today, there is no effective treatment in its chronic stage. We have recently identified 134 FDA approved drugs with potential antitrypanosomal activity. In this paper, we propose a novel method for selecting combinations of drugs (drug cocktails), to provide a more effective treatment against Chagas disease. We define three measures to evaluate the predicted performance of a cocktail, establishing in this way a mathematical foundation for its analysis. This allows us to model the drug cocktail selection as a multiobjective optimisation problem, that we show can be solved efficiently with state-of-the-art evolutionary algorithms. Our analysis retrieves 57 drug cocktails containing between 2 and 6 drugs. We discuss the improvement of the cocktail selection given by our method, and the application of this approach to the identification of cocktails against other parasitic diseases.
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