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Robustness Testing of Microemulsion Liquid Chromatographic Separation of Simvastatin and its Impurities

Samo za registrovane korisnike
2009
Autori
Malenović, Anđelija
Ivanović, Darko
Jančić-Stojanović, Biljana
Medenica, Mirjana
Članak u časopisu (Objavljena verzija)
Metapodaci
Prikaz svih podataka o dokumentu
Apstrakt
Liquid chromatography employing the microemulsion as eluent was applied for the analysis of simvastatin and its six impurities. Previously, the optimized and validated method was tested to prove the method's capability to perform during the small changes of important parameters. In this paper, influence of parameters tipical for microemulsion liquid chromatography (MELC) on the method's robustness was presented. For the results evaluation, and presentation, two statistical methods were applied. In order to designate the most convinient one, multiple regression (MR) and artificial neural networks (ANN) were applied and compared. A set of experiments was defined by the central composite design (CCD). Indepedent variables (SDS, n-buthanol and diisopropyl ether content) and dependent variables (retention factors of investigated substances) were the framework for both, MR and ANN. This study demonstrated that MR and radial basis function ANN are useful tools in understanding the effects of ...the investigated factors on the chromatographic system and definition of the robustness limits.

Ključne reči:
Artificial neural networks / MELC / Multiple regression / Robustness testing / Simvastatin
Izvor:
Journal of Liquid Chromatography & Related Technologies, 2009, 32, 6, 874-889
Izdavač:
  • Taylor & Francis Inc, Philadelphia
Finansiranje / projekti:
  • Formulisanje i Karakterizacija separacionih sistema za modelovanje retencionog ponašanja lekovitih supstancija uz hemometrijsku evaluaciju (RS-142077)

DOI: 10.1080/10826070902768161

ISSN: 1082-6076

WoS: 000263646300009

Scopus: 2-s2.0-61649084961
[ Google Scholar ]
10
7
URI
https://farfar.pharmacy.bg.ac.rs/handle/123456789/1248
Kolekcije
  • Radovi istraživača / Researchers’ publications
Institucija/grupa
Pharmacy
TY  - JOUR
AU  - Malenović, Anđelija
AU  - Ivanović, Darko
AU  - Jančić-Stojanović, Biljana
AU  - Medenica, Mirjana
PY  - 2009
UR  - https://farfar.pharmacy.bg.ac.rs/handle/123456789/1248
AB  - Liquid chromatography employing the microemulsion as eluent was applied for the analysis of simvastatin and its six impurities. Previously, the optimized and validated method was tested to prove the method's capability to perform during the small changes of important parameters. In this paper, influence of parameters tipical for microemulsion liquid chromatography (MELC) on the method's robustness was presented. For the results evaluation, and presentation, two statistical methods were applied. In order to designate the most convinient one, multiple regression (MR) and artificial neural networks (ANN) were applied and compared. A set of experiments was defined by the central composite design (CCD). Indepedent variables (SDS, n-buthanol and diisopropyl ether content) and dependent variables (retention factors of investigated substances) were the framework for both, MR and ANN. This study demonstrated that MR and radial basis function ANN are useful tools in understanding the effects of the investigated factors on the chromatographic system and definition of the robustness limits.
PB  - Taylor & Francis Inc, Philadelphia
T2  - Journal of Liquid Chromatography & Related Technologies
T1  - Robustness Testing of Microemulsion Liquid Chromatographic Separation of Simvastatin and its Impurities
VL  - 32
IS  - 6
SP  - 874
EP  - 889
DO  - 10.1080/10826070902768161
ER  - 
@article{
author = "Malenović, Anđelija and Ivanović, Darko and Jančić-Stojanović, Biljana and Medenica, Mirjana",
year = "2009",
abstract = "Liquid chromatography employing the microemulsion as eluent was applied for the analysis of simvastatin and its six impurities. Previously, the optimized and validated method was tested to prove the method's capability to perform during the small changes of important parameters. In this paper, influence of parameters tipical for microemulsion liquid chromatography (MELC) on the method's robustness was presented. For the results evaluation, and presentation, two statistical methods were applied. In order to designate the most convinient one, multiple regression (MR) and artificial neural networks (ANN) were applied and compared. A set of experiments was defined by the central composite design (CCD). Indepedent variables (SDS, n-buthanol and diisopropyl ether content) and dependent variables (retention factors of investigated substances) were the framework for both, MR and ANN. This study demonstrated that MR and radial basis function ANN are useful tools in understanding the effects of the investigated factors on the chromatographic system and definition of the robustness limits.",
publisher = "Taylor & Francis Inc, Philadelphia",
journal = "Journal of Liquid Chromatography & Related Technologies",
title = "Robustness Testing of Microemulsion Liquid Chromatographic Separation of Simvastatin and its Impurities",
volume = "32",
number = "6",
pages = "874-889",
doi = "10.1080/10826070902768161"
}
Malenović, A., Ivanović, D., Jančić-Stojanović, B.,& Medenica, M.. (2009). Robustness Testing of Microemulsion Liquid Chromatographic Separation of Simvastatin and its Impurities. in Journal of Liquid Chromatography & Related Technologies
Taylor & Francis Inc, Philadelphia., 32(6), 874-889.
https://doi.org/10.1080/10826070902768161
Malenović A, Ivanović D, Jančić-Stojanović B, Medenica M. Robustness Testing of Microemulsion Liquid Chromatographic Separation of Simvastatin and its Impurities. in Journal of Liquid Chromatography & Related Technologies. 2009;32(6):874-889.
doi:10.1080/10826070902768161 .
Malenović, Anđelija, Ivanović, Darko, Jančić-Stojanović, Biljana, Medenica, Mirjana, "Robustness Testing of Microemulsion Liquid Chromatographic Separation of Simvastatin and its Impurities" in Journal of Liquid Chromatography & Related Technologies, 32, no. 6 (2009):874-889,
https://doi.org/10.1080/10826070902768161 . .

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