Optimization of Artificial Neural Networks for Modeling of Atorvastatin and Its Impurities Retention in Micellar Liquid Chromatography
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2011
Authors
Malenović, Anđelija
Jančić-Stojanović, Biljana

Kostić, Nada
Ivanović, Darko
Medenica, Mirjana
Article (Published version)

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Artificial Neural Networks (ANNs) present a powerful tool for the modeling of chromatographic retention. In this paper, the main objective was to use ANNs as a tool in modeling of atorvastatin and its impurities' retention in a micellar liquid chromatography (MLC) protocol. Factors referred to MLC were evaluated through 30 experiments defined by the Central Composite Design. In this manner, 5-x-3 topology as a starting point for ANNs' optimization was defined too. In the next step, in order to set the network with the best performance, network optimization was done. In the first part, the number of nodes in the hidden layer and the number of experimental data points in training set were simultaneously varied, and their importance was estimated with suitable statistical parameters. Furthermore, a series of training algorithms was applied to the current network. The Back Propagation, Conjugate Gradient-descent, Quick Propagation, Quasi-Newton, and Delta-bar-Delta algorithms were used to ...obtain the optimal network. Finally, the predictive ability of the optimized neural network was confirmed through several statistical tests. The obtained network showed high ability to predict chromatographic retention of atorvastatin and its impurities in MLC.
Keywords:
Micellar liquid chromatography / Artificial neural networks / Network's optimization / Atorvastatin / ImpuritiesSource:
Chromatographia, 2011, 73, 9-10, 993-998Publisher:
- Springer Heidelberg, Heidelberg
Funding / projects:
- Modelling of different chromatographic systems with chemometrical approach in pharmaceutical analysis (RS-172052)
DOI: 10.1007/s10337-011-1994-6
ISSN: 0009-5893
WoS: 000289300500019
Scopus: 2-s2.0-79958250797
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Institution/Community
PharmacyTY - JOUR AU - Malenović, Anđelija AU - Jančić-Stojanović, Biljana AU - Kostić, Nada AU - Ivanović, Darko AU - Medenica, Mirjana PY - 2011 UR - https://farfar.pharmacy.bg.ac.rs/handle/123456789/1521 AB - Artificial Neural Networks (ANNs) present a powerful tool for the modeling of chromatographic retention. In this paper, the main objective was to use ANNs as a tool in modeling of atorvastatin and its impurities' retention in a micellar liquid chromatography (MLC) protocol. Factors referred to MLC were evaluated through 30 experiments defined by the Central Composite Design. In this manner, 5-x-3 topology as a starting point for ANNs' optimization was defined too. In the next step, in order to set the network with the best performance, network optimization was done. In the first part, the number of nodes in the hidden layer and the number of experimental data points in training set were simultaneously varied, and their importance was estimated with suitable statistical parameters. Furthermore, a series of training algorithms was applied to the current network. The Back Propagation, Conjugate Gradient-descent, Quick Propagation, Quasi-Newton, and Delta-bar-Delta algorithms were used to obtain the optimal network. Finally, the predictive ability of the optimized neural network was confirmed through several statistical tests. The obtained network showed high ability to predict chromatographic retention of atorvastatin and its impurities in MLC. PB - Springer Heidelberg, Heidelberg T2 - Chromatographia T1 - Optimization of Artificial Neural Networks for Modeling of Atorvastatin and Its Impurities Retention in Micellar Liquid Chromatography VL - 73 IS - 9-10 SP - 993 EP - 998 DO - 10.1007/s10337-011-1994-6 ER -
@article{ author = "Malenović, Anđelija and Jančić-Stojanović, Biljana and Kostić, Nada and Ivanović, Darko and Medenica, Mirjana", year = "2011", abstract = "Artificial Neural Networks (ANNs) present a powerful tool for the modeling of chromatographic retention. In this paper, the main objective was to use ANNs as a tool in modeling of atorvastatin and its impurities' retention in a micellar liquid chromatography (MLC) protocol. Factors referred to MLC were evaluated through 30 experiments defined by the Central Composite Design. In this manner, 5-x-3 topology as a starting point for ANNs' optimization was defined too. In the next step, in order to set the network with the best performance, network optimization was done. In the first part, the number of nodes in the hidden layer and the number of experimental data points in training set were simultaneously varied, and their importance was estimated with suitable statistical parameters. Furthermore, a series of training algorithms was applied to the current network. The Back Propagation, Conjugate Gradient-descent, Quick Propagation, Quasi-Newton, and Delta-bar-Delta algorithms were used to obtain the optimal network. Finally, the predictive ability of the optimized neural network was confirmed through several statistical tests. The obtained network showed high ability to predict chromatographic retention of atorvastatin and its impurities in MLC.", publisher = "Springer Heidelberg, Heidelberg", journal = "Chromatographia", title = "Optimization of Artificial Neural Networks for Modeling of Atorvastatin and Its Impurities Retention in Micellar Liquid Chromatography", volume = "73", number = "9-10", pages = "993-998", doi = "10.1007/s10337-011-1994-6" }
Malenović, A., Jančić-Stojanović, B., Kostić, N., Ivanović, D.,& Medenica, M.. (2011). Optimization of Artificial Neural Networks for Modeling of Atorvastatin and Its Impurities Retention in Micellar Liquid Chromatography. in Chromatographia Springer Heidelberg, Heidelberg., 73(9-10), 993-998. https://doi.org/10.1007/s10337-011-1994-6
Malenović A, Jančić-Stojanović B, Kostić N, Ivanović D, Medenica M. Optimization of Artificial Neural Networks for Modeling of Atorvastatin and Its Impurities Retention in Micellar Liquid Chromatography. in Chromatographia. 2011;73(9-10):993-998. doi:10.1007/s10337-011-1994-6 .
Malenović, Anđelija, Jančić-Stojanović, Biljana, Kostić, Nada, Ivanović, Darko, Medenica, Mirjana, "Optimization of Artificial Neural Networks for Modeling of Atorvastatin and Its Impurities Retention in Micellar Liquid Chromatography" in Chromatographia, 73, no. 9-10 (2011):993-998, https://doi.org/10.1007/s10337-011-1994-6 . .