Application of artificial neural network to predict the retention time of drug metabolites in two-dimensional liquid chromatography

Authors


Correspondence to: H. Noorizadeh, Faculty of Science, Ilam Branch, Islamic Azad University, Ilam, Iran. E-mail: hadinoorizadeh@yahoo.com

Abstract

Genetic algorithm and partial least square (GA-PLS) and Levenberg- Marquardt artificial neural network (L-M ANN) techniques were used to investigate the correlation between retention time and descriptors for drug metabolites which obtained by two-dimensional liquid chromatography. The applied internal (leave-group-out cross validation (LGO-CV)) and external (test set) validation methods were used for the predictive power of four models. Both methods resulted in accurate prediction whereas more accurate results were obtained by L-M ANN model. The best model obtained from L-M ANN showed a good R2 value (determination coefficient between observed and predicted values) for all compounds, which was superior to GA-PLS models. Copyright © 2011 John Wiley & Sons, Ltd.

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