The Chemometric Study and Quantitative Structure Retention Relationship Modeling of Liquid Chromatography Separation of Ziprasidone Components
Само за регистроване кориснике
2012
Чланак у часопису (Објављена верзија)
Метаподаци
Приказ свих података о документуАпстракт
Optimization of the experimental conditions of a novel HPLC method for determination of the impurity levels with ziprasidone (in bulk substance and pharmaceutical dosage forms) was performed with use of Multi-Layer Perceptron (MLP) Artificial Neural Networks (ANN) and Response Surface Plots. The obtained experimental conditions were further used to test a set of 20 reversed-phase columns for their selectivity towards ziprasidone components by use of the principal component analysis (PCA) and hierarchical clustering analysis (HCA). The obtained HPLC retention times of ziprasidone and its impurities (Imp I-V) along with the computed molecular parameters of the examined compounds were further used in the Quantitative Structure Retention Relationship (QSRR) study. The performed QSRR study has selected the LogD(pH) (1.5), LogD(pH 2.5), LogD(pH 4.0), LogP, MS, and SAS parameters as descriptors of the chromatographic behavior of ziprasidone components. The developed QSRR model can be very use...ful in the t(R) prediction for the ziprasidone derivatives (impurities, degradation products, and metabolites). As the performed LC-MS study of the test solution has confirmed that the unknown impurity (t(R): 11.270 min) in the test solution is the TS1, one from two candidates predicted by QSRR (TS1 and TS5), the high prediction potential of the created QSRR models has been proved.
Кључне речи:
ANN / HCA / HPLC / PCA / PLS / QSRR / ziprasidoneИзвор:
Combinatorial Chemistry & High Throughput Screening, 2012, 15, 9, 730-744Издавач:
- Bentham Science Publ Ltd, Sharjah
Финансирање / пројекти:
- Синтеза, квантитативни однос између структуре и дејства, физичко-хемијска карактеризација и анализа фармаколошки активних супстанци (RS-MESTD-Basic Research (BR or ON)-172033)
DOI: 10.2174/138620712803519699
ISSN: 1386-2073
PubMed: 22934948
WoS: 000314821100006
Scopus: 2-s2.0-84870406306
Институција/група
PharmacyTY - JOUR AU - Nikolić, Katarina AU - Pavlović, Marija AU - Smolinski, Adam AU - Agbaba, Danica PY - 2012 UR - https://farfar.pharmacy.bg.ac.rs/handle/123456789/1670 AB - Optimization of the experimental conditions of a novel HPLC method for determination of the impurity levels with ziprasidone (in bulk substance and pharmaceutical dosage forms) was performed with use of Multi-Layer Perceptron (MLP) Artificial Neural Networks (ANN) and Response Surface Plots. The obtained experimental conditions were further used to test a set of 20 reversed-phase columns for their selectivity towards ziprasidone components by use of the principal component analysis (PCA) and hierarchical clustering analysis (HCA). The obtained HPLC retention times of ziprasidone and its impurities (Imp I-V) along with the computed molecular parameters of the examined compounds were further used in the Quantitative Structure Retention Relationship (QSRR) study. The performed QSRR study has selected the LogD(pH) (1.5), LogD(pH 2.5), LogD(pH 4.0), LogP, MS, and SAS parameters as descriptors of the chromatographic behavior of ziprasidone components. The developed QSRR model can be very useful in the t(R) prediction for the ziprasidone derivatives (impurities, degradation products, and metabolites). As the performed LC-MS study of the test solution has confirmed that the unknown impurity (t(R): 11.270 min) in the test solution is the TS1, one from two candidates predicted by QSRR (TS1 and TS5), the high prediction potential of the created QSRR models has been proved. PB - Bentham Science Publ Ltd, Sharjah T2 - Combinatorial Chemistry & High Throughput Screening T1 - The Chemometric Study and Quantitative Structure Retention Relationship Modeling of Liquid Chromatography Separation of Ziprasidone Components VL - 15 IS - 9 SP - 730 EP - 744 DO - 10.2174/138620712803519699 ER -
@article{ author = "Nikolić, Katarina and Pavlović, Marija and Smolinski, Adam and Agbaba, Danica", year = "2012", abstract = "Optimization of the experimental conditions of a novel HPLC method for determination of the impurity levels with ziprasidone (in bulk substance and pharmaceutical dosage forms) was performed with use of Multi-Layer Perceptron (MLP) Artificial Neural Networks (ANN) and Response Surface Plots. The obtained experimental conditions were further used to test a set of 20 reversed-phase columns for their selectivity towards ziprasidone components by use of the principal component analysis (PCA) and hierarchical clustering analysis (HCA). The obtained HPLC retention times of ziprasidone and its impurities (Imp I-V) along with the computed molecular parameters of the examined compounds were further used in the Quantitative Structure Retention Relationship (QSRR) study. The performed QSRR study has selected the LogD(pH) (1.5), LogD(pH 2.5), LogD(pH 4.0), LogP, MS, and SAS parameters as descriptors of the chromatographic behavior of ziprasidone components. The developed QSRR model can be very useful in the t(R) prediction for the ziprasidone derivatives (impurities, degradation products, and metabolites). As the performed LC-MS study of the test solution has confirmed that the unknown impurity (t(R): 11.270 min) in the test solution is the TS1, one from two candidates predicted by QSRR (TS1 and TS5), the high prediction potential of the created QSRR models has been proved.", publisher = "Bentham Science Publ Ltd, Sharjah", journal = "Combinatorial Chemistry & High Throughput Screening", title = "The Chemometric Study and Quantitative Structure Retention Relationship Modeling of Liquid Chromatography Separation of Ziprasidone Components", volume = "15", number = "9", pages = "730-744", doi = "10.2174/138620712803519699" }
Nikolić, K., Pavlović, M., Smolinski, A.,& Agbaba, D.. (2012). The Chemometric Study and Quantitative Structure Retention Relationship Modeling of Liquid Chromatography Separation of Ziprasidone Components. in Combinatorial Chemistry & High Throughput Screening Bentham Science Publ Ltd, Sharjah., 15(9), 730-744. https://doi.org/10.2174/138620712803519699
Nikolić K, Pavlović M, Smolinski A, Agbaba D. The Chemometric Study and Quantitative Structure Retention Relationship Modeling of Liquid Chromatography Separation of Ziprasidone Components. in Combinatorial Chemistry & High Throughput Screening. 2012;15(9):730-744. doi:10.2174/138620712803519699 .
Nikolić, Katarina, Pavlović, Marija, Smolinski, Adam, Agbaba, Danica, "The Chemometric Study and Quantitative Structure Retention Relationship Modeling of Liquid Chromatography Separation of Ziprasidone Components" in Combinatorial Chemistry & High Throughput Screening, 15, no. 9 (2012):730-744, https://doi.org/10.2174/138620712803519699 . .