TY  - CONF
AU  - Čarapić, Marija
AU  - Nikolić, Katarina
AU  - Smolinski, Adam
AU  - Agbaba, Danica
PY  - 2018
UR  - https://farfar.pharmacy.bg.ac.rs/handle/123456789/4876
AB  - Ziprasidon je novi atipični antipsihotik druge generacije, koji deluje kao
antagonista na serotoninskim i dopaminskim receptorima, i inhibira preuzimanje
norepinefrina. Glavni cilj hemometrijske studije je ispitivanje selektivnosti 20 reverznofaznih
(RP) stacionarnih faza u odnosu na ziprazidon i šest nečistoća ((I‐V) i
nepoznata). Velika strukturna sličnost ziprasidona i nečistoće II bila je ključni problem i
razdvajanje kritičnog para je bilo odlučujuće za odabir RP stacionarne faze.
Za analizu glavnih komponenti (PCA) korišćen je matematički program Soft
Independent Modeling of Class Analogy SIMCA P+ 12.0, a za analizu hijerarhijskog
grupisanja (HCA) korišćen je program MATLAB ver. 6.5.
Ispitivanje selektivnosti 20 RP stacionarnih faza je vršeno pri dobijenim
optimalnim eksperimentalnim uslovima (25 ºC; pH: 2,5; cTEA: 1% i cKH2PO4: 50mM) u
odnosu na ispitivana jedinjenja. Eksperimentalno dobijeni hromatografski parametri
(broj teoretskih platoa‐N, faktor simetrije pika ‐SF, rezolucija ‐Rs i faktor selektivnosti ‐
α između jedinjenja koja se blizu eluiraju) na 20 RP stacionarnih faza analizirani su
primenom PCA i HCA analiza.
Grafikoni rezultata i PCA koeficijenata variabli za PC1(osnovna komponeta 1) i
PC2 (osnovna komponeta 2) pokazuju glavne razlike između svih 20 RP‐kolona i glavne
sličnosti između hromatografskih parametara. Rs i α su odabrani kao najznačajniji
parametri za izbor stacionarne faze. Dobijeni dendogrami pokazali su tri glavne grupe
za stacionarne faze i četiri grupe za hromatografske parametre. Dendogrami RP kolona
i hromatografskih parametara su prikazani i obojenom mapom što je jednostavnija
metoda vizuelizacije.
Određene su RP stacionarne faze posebno selektivne za efikasno razdvajanje
ziprasidona i strukturno sličnih jedinjenja primenom PCA i HCA (grupa 1 PCA i grupa C
AHC):Waters Spherisorb® ODS1, Waters Spherisorb® ODS2 i Nucleosil® 100‐5 C18.
Dobijeni podaci su u skladu sa eksperimentalnim rezultatima. Odabrana je Waters
Spherisorb® ODS 1 kolona za HPLC metodu u odnosu na najbolju SF i faktor retencije
(k’).
AB  - Ziprasidone is a novel „atypical” or „second generation” antipsychotic drug
which acts primarily through serotonergic and dopaminergic receptor antagonism, and
as an inhibitor of the norepinephrine reuptake. The main aims of the presented
chemometric study was to test selectivity of the set of 20 Reversed‐phase (RP) ‐
columns towards ziprasidone and its six impurities ((I‐V) and one unknown).
Separation of structurally similar pair of ziprasidone/impurity II caused analytical
problems and was decisive for the selection of the suitable RP‐column.
The Principal Component Analysis (PCA) for column classification was done with
use of SIMCA P+ 12.0 program and Hierarchical Clustering Analysis (HCA) with use of
MATLAB ver. 6.5. with additional algorithms.
The obtained optimal chromatographic conditions (25C, pH 2,5, cTEA 1% and
cKH2PO4 50 mM) were used to test a set of 20 RP‐columns. Plate numbers (N),
symmetry factors (SF), resolution (Rs) and selectivity (α) of investigated compounds
were subjected to PCA and HCA analysis. Score plot and loading plots PC1 (principal
component 1) vs PC2 (principal component 2) visualize the main differences between
all 20 RP‐columns and main similarities between hromatographic parameters,
respectively. The Rs and α were selected as the most significant for the column
selection. The obtained dendrograms reveal three distinct clusters of RP‐columns and
four clusters of chromatographic parameters. The color map of data was used as a
simpler presentation of the dendrograms of RP‐columns and chromatographic
parameters.
The RP‐columns selective for the efficient separation of ziprasidone and its
structurally related compounds were defined by PCA and HCA (group 1 in PCA study
and same cluster C in HCA study) : Waters Spherisorb® ODS1, Waters Spherisorb®
ODS2 and Nucleosil® 100‐5 C18. The results were in accordance with experimentally
obtained results. Finally, the column Waters Spherisorb® ODS 1 was selected for the
HPLC method due to best SF and retention factor (k’).
PB  - Savez farmaceutskih udruženja Srbije (SFUS)
C3  - Arhiv za farmaciju
T1  - Primena metoda multivarijantnih analiza glavnih komponenti i hijerarhijskog grupisanja u ispitivanju razdvajanja jedinjenja ziprasidona tečnom hromatografijom
T1  - Modeling of liquid chromatography separation of ziprasidone compounds using multivariate methods of principal component and hierarchical clustering analysis
VL  - 68
IS  - 3
SP  - 411
EP  - 412
UR  - https://hdl.handle.net/21.15107/rcub_farfar_4876
ER  - 

@conference{
author = "Čarapić, Marija and Nikolić, Katarina and Smolinski, Adam and Agbaba, Danica",
year = "2018",
abstract = "Ziprasidon je novi atipični antipsihotik druge generacije, koji deluje kao
antagonista na serotoninskim i dopaminskim receptorima, i inhibira preuzimanje
norepinefrina. Glavni cilj hemometrijske studije je ispitivanje selektivnosti 20 reverznofaznih
(RP) stacionarnih faza u odnosu na ziprazidon i šest nečistoća ((I‐V) i
nepoznata). Velika strukturna sličnost ziprasidona i nečistoće II bila je ključni problem i
razdvajanje kritičnog para je bilo odlučujuće za odabir RP stacionarne faze.
Za analizu glavnih komponenti (PCA) korišćen je matematički program Soft
Independent Modeling of Class Analogy SIMCA P+ 12.0, a za analizu hijerarhijskog
grupisanja (HCA) korišćen je program MATLAB ver. 6.5.
Ispitivanje selektivnosti 20 RP stacionarnih faza je vršeno pri dobijenim
optimalnim eksperimentalnim uslovima (25 ºC; pH: 2,5; cTEA: 1% i cKH2PO4: 50mM) u
odnosu na ispitivana jedinjenja. Eksperimentalno dobijeni hromatografski parametri
(broj teoretskih platoa‐N, faktor simetrije pika ‐SF, rezolucija ‐Rs i faktor selektivnosti ‐
α između jedinjenja koja se blizu eluiraju) na 20 RP stacionarnih faza analizirani su
primenom PCA i HCA analiza.
Grafikoni rezultata i PCA koeficijenata variabli za PC1(osnovna komponeta 1) i
PC2 (osnovna komponeta 2) pokazuju glavne razlike između svih 20 RP‐kolona i glavne
sličnosti između hromatografskih parametara. Rs i α su odabrani kao najznačajniji
parametri za izbor stacionarne faze. Dobijeni dendogrami pokazali su tri glavne grupe
za stacionarne faze i četiri grupe za hromatografske parametre. Dendogrami RP kolona
i hromatografskih parametara su prikazani i obojenom mapom što je jednostavnija
metoda vizuelizacije.
Određene su RP stacionarne faze posebno selektivne za efikasno razdvajanje
ziprasidona i strukturno sličnih jedinjenja primenom PCA i HCA (grupa 1 PCA i grupa C
AHC):Waters Spherisorb® ODS1, Waters Spherisorb® ODS2 i Nucleosil® 100‐5 C18.
Dobijeni podaci su u skladu sa eksperimentalnim rezultatima. Odabrana je Waters
Spherisorb® ODS 1 kolona za HPLC metodu u odnosu na najbolju SF i faktor retencije
(k’)., Ziprasidone is a novel „atypical” or „second generation” antipsychotic drug
which acts primarily through serotonergic and dopaminergic receptor antagonism, and
as an inhibitor of the norepinephrine reuptake. The main aims of the presented
chemometric study was to test selectivity of the set of 20 Reversed‐phase (RP) ‐
columns towards ziprasidone and its six impurities ((I‐V) and one unknown).
Separation of structurally similar pair of ziprasidone/impurity II caused analytical
problems and was decisive for the selection of the suitable RP‐column.
The Principal Component Analysis (PCA) for column classification was done with
use of SIMCA P+ 12.0 program and Hierarchical Clustering Analysis (HCA) with use of
MATLAB ver. 6.5. with additional algorithms.
The obtained optimal chromatographic conditions (25C, pH 2,5, cTEA 1% and
cKH2PO4 50 mM) were used to test a set of 20 RP‐columns. Plate numbers (N),
symmetry factors (SF), resolution (Rs) and selectivity (α) of investigated compounds
were subjected to PCA and HCA analysis. Score plot and loading plots PC1 (principal
component 1) vs PC2 (principal component 2) visualize the main differences between
all 20 RP‐columns and main similarities between hromatographic parameters,
respectively. The Rs and α were selected as the most significant for the column
selection. The obtained dendrograms reveal three distinct clusters of RP‐columns and
four clusters of chromatographic parameters. The color map of data was used as a
simpler presentation of the dendrograms of RP‐columns and chromatographic
parameters.
The RP‐columns selective for the efficient separation of ziprasidone and its
structurally related compounds were defined by PCA and HCA (group 1 in PCA study
and same cluster C in HCA study) : Waters Spherisorb® ODS1, Waters Spherisorb®
ODS2 and Nucleosil® 100‐5 C18. The results were in accordance with experimentally
obtained results. Finally, the column Waters Spherisorb® ODS 1 was selected for the
HPLC method due to best SF and retention factor (k’).",
publisher = "Savez farmaceutskih udruženja Srbije (SFUS)",
journal = "Arhiv za farmaciju",
title = "Primena metoda multivarijantnih analiza glavnih komponenti i hijerarhijskog grupisanja u ispitivanju razdvajanja jedinjenja ziprasidona tečnom hromatografijom, Modeling of liquid chromatography separation of ziprasidone compounds using multivariate methods of principal component and hierarchical clustering analysis",
volume = "68",
number = "3",
pages = "411-412",
url = "https://hdl.handle.net/21.15107/rcub_farfar_4876"
}

Čarapić, M., Nikolić, K., Smolinski, A.,& Agbaba, D.. (2018). Primena metoda multivarijantnih analiza glavnih komponenti i hijerarhijskog grupisanja u ispitivanju razdvajanja jedinjenja ziprasidona tečnom hromatografijom. in Arhiv za farmaciju
Savez farmaceutskih udruženja Srbije (SFUS)., 68(3), 411-412.
https://hdl.handle.net/21.15107/rcub_farfar_4876

Čarapić M, Nikolić K, Smolinski A, Agbaba D. Primena metoda multivarijantnih analiza glavnih komponenti i hijerarhijskog grupisanja u ispitivanju razdvajanja jedinjenja ziprasidona tečnom hromatografijom. in Arhiv za farmaciju. 2018;68(3):411-412.
https://hdl.handle.net/21.15107/rcub_farfar_4876 .

Čarapić, Marija, Nikolić, Katarina, Smolinski, Adam, Agbaba, Danica, "Primena metoda multivarijantnih analiza glavnih komponenti i hijerarhijskog grupisanja u ispitivanju razdvajanja jedinjenja ziprasidona tečnom hromatografijom" in Arhiv za farmaciju, 68, no. 3 (2018):411-412,
https://hdl.handle.net/21.15107/rcub_farfar_4876 .

TY  - JOUR
AU  - Nikolić, Katarina
AU  - Filipić, Slavica
AU  - Smolinski, Adam
AU  - Kaliszan, Roman
AU  - Agbaba, Danica
PY  - 2013
UR  - https://farfar.pharmacy.bg.ac.rs/handle/123456789/1901
AB  - PURPOSE. Rate of brain penetration (logPS), brain/plasma equilibration rate (logPS-brain), and extent of blood-brain barrier permeation (logBB) of 29 alpha-adrenergic and imidazoline-receptors ligands were examined in Quantitative-Structure-Property Relationship (QSPR) study. METHODS. Experimentally determined chromatographic retention data (logKw at pH 4.4, slope (S) at pH 4.4, logKw at pH 7.4, slope (S) at pH 7.4, logKw at pH 9.1, and slope (S) at pH 9.1) and capillary electrophoresis migration parameters (mu(eff) at pH 4.4, mu(eff) at pH 7.4, and mu(eff) at pH 9.1), together with calculated molecular descriptors, were used as independent variables in the QSPR study by use of partial least square (PLS) methodology. RESULTS. Predictive potential of the formed QSPR models, QSPR(logPS), QSPR(logPS-brain), QSPR(logBB), was confirmed by cross- and external validation. Hydrophilicity (Hy) and H-indices (H7m) were selected as significant parameters negatively correlated with both logPS and logPS-brain, while topological polar surface area (TPSA(NO)) was chosen as molecular descriptor negatively correlated with both logPS and logBB. The principal component analysis (PCA) and hierarchical clustering analysis (HCA) were applied to cluster examined drugs based on their chromatographic, electrophoretic and molecular properties. Significant positive correlations were obtained between the slope (S) at pH 7.4 and logBB in A/B cluster and between the logKw at pH 9.1 and logPS in C/D cluster. CONCLUSIONS. Results of the QSPR, clustering and correlation studies could be used as novel tool for evaluation of blood-brain barrier permeation of related alpha-adrenergic/imidazoline receptor ligands.
PB  - Canadian Soc Pharmaceutical Sciences, Edmonton
T2  - Journal of Pharmacy and Pharmaceutical Sciences
T1  - Partial Least Square and Hierarchical Clustering in ADMET Modeling: Prediction of Blood - Brain Barrier Permeation of alpha-Adrenergic and Imidazoline Receptor Ligands
VL  - 16
IS  - 4
SP  - 622
EP  - 647
DO  - 10.18433/J3JK5P
ER  - 

@article{
author = "Nikolić, Katarina and Filipić, Slavica and Smolinski, Adam and Kaliszan, Roman and Agbaba, Danica",
year = "2013",
abstract = "PURPOSE. Rate of brain penetration (logPS), brain/plasma equilibration rate (logPS-brain), and extent of blood-brain barrier permeation (logBB) of 29 alpha-adrenergic and imidazoline-receptors ligands were examined in Quantitative-Structure-Property Relationship (QSPR) study. METHODS. Experimentally determined chromatographic retention data (logKw at pH 4.4, slope (S) at pH 4.4, logKw at pH 7.4, slope (S) at pH 7.4, logKw at pH 9.1, and slope (S) at pH 9.1) and capillary electrophoresis migration parameters (mu(eff) at pH 4.4, mu(eff) at pH 7.4, and mu(eff) at pH 9.1), together with calculated molecular descriptors, were used as independent variables in the QSPR study by use of partial least square (PLS) methodology. RESULTS. Predictive potential of the formed QSPR models, QSPR(logPS), QSPR(logPS-brain), QSPR(logBB), was confirmed by cross- and external validation. Hydrophilicity (Hy) and H-indices (H7m) were selected as significant parameters negatively correlated with both logPS and logPS-brain, while topological polar surface area (TPSA(NO)) was chosen as molecular descriptor negatively correlated with both logPS and logBB. The principal component analysis (PCA) and hierarchical clustering analysis (HCA) were applied to cluster examined drugs based on their chromatographic, electrophoretic and molecular properties. Significant positive correlations were obtained between the slope (S) at pH 7.4 and logBB in A/B cluster and between the logKw at pH 9.1 and logPS in C/D cluster. CONCLUSIONS. Results of the QSPR, clustering and correlation studies could be used as novel tool for evaluation of blood-brain barrier permeation of related alpha-adrenergic/imidazoline receptor ligands.",
publisher = "Canadian Soc Pharmaceutical Sciences, Edmonton",
journal = "Journal of Pharmacy and Pharmaceutical Sciences",
title = "Partial Least Square and Hierarchical Clustering in ADMET Modeling: Prediction of Blood - Brain Barrier Permeation of alpha-Adrenergic and Imidazoline Receptor Ligands",
volume = "16",
number = "4",
pages = "622-647",
doi = "10.18433/J3JK5P"
}

Nikolić, K., Filipić, S., Smolinski, A., Kaliszan, R.,& Agbaba, D.. (2013). Partial Least Square and Hierarchical Clustering in ADMET Modeling: Prediction of Blood - Brain Barrier Permeation of alpha-Adrenergic and Imidazoline Receptor Ligands. in Journal of Pharmacy and Pharmaceutical Sciences
Canadian Soc Pharmaceutical Sciences, Edmonton., 16(4), 622-647.
https://doi.org/10.18433/J3JK5P

Nikolić K, Filipić S, Smolinski A, Kaliszan R, Agbaba D. Partial Least Square and Hierarchical Clustering in ADMET Modeling: Prediction of Blood - Brain Barrier Permeation of alpha-Adrenergic and Imidazoline Receptor Ligands. in Journal of Pharmacy and Pharmaceutical Sciences. 2013;16(4):622-647.
doi:10.18433/J3JK5P .

Nikolić, Katarina, Filipić, Slavica, Smolinski, Adam, Kaliszan, Roman, Agbaba, Danica, "Partial Least Square and Hierarchical Clustering in ADMET Modeling: Prediction of Blood - Brain Barrier Permeation of alpha-Adrenergic and Imidazoline Receptor Ligands" in Journal of Pharmacy and Pharmaceutical Sciences, 16, no. 4 (2013):622-647,
https://doi.org/10.18433/J3JK5P . .

TY  - 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 . .