Statistical Assessment of Solvent Mixture Models Used for Separation of Biological Active Compounds

Two mathematical models with seven and six parameters have been created for use as methods for identification of the optimum mobile phase in chromatographic separations. A series of chromatographic response functions were proposed and implemented in order to assess and validate the models. The asses...

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Main Authors: Lorentz Jäntschi, Claudia V. Cimpoiu, Elena M. Pică, Sorana D. Bolboacă
Format: Article
Language:English
Published: MDPI AG 2008-08-01
Series:Molecules
Subjects:
Online Access:http://www.mdpi.com/1420-3049/13/8/1617/
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spelling doaj-94a3f10eac9b4d37bd70b6668f7599972020-11-25T00:53:48ZengMDPI AGMolecules1420-30492008-08-011381617163910.3390/molecules13081617Statistical Assessment of Solvent Mixture Models Used for Separation of Biological Active CompoundsLorentz JäntschiClaudia V. CimpoiuElena M. PicăSorana D. BolboacăTwo mathematical models with seven and six parameters have been created for use as methods for identification of the optimum mobile phase in chromatographic separations. A series of chromatographic response functions were proposed and implemented in order to assess and validate the models. The assessment was performed on a set of androstane isomers. Pearson, Spearman, Kendall tau-a,b,c and Goodman-Kruskal correlation coefficients were used in order to identify and to quantify the link and its nature (quantitative, categorical, semi-quantitative, both quantitative and categorical) between experimental values and the values estimated by the mathematical models. The study revealed that the six parameter model is valid and reliable for five chromatographic response factors (retardation factor, retardation factor ordered ascending by the chromatographic peak, resolution of pairs of compound, resolution matrix of successive chromatographic peaks, and quality factor). Furthermore, the model could be used as an instrument in analysis of the quality of experimental data. The results obtained by applying the model with six parameters for deviations of rank sums suggest that the data of the experiment no. 8 are questionable.http://www.mdpi.com/1420-3049/13/8/1617/Mathematical modelchromatographic response functionsstatistical assessmentcorrelation.
collection DOAJ
language English
format Article
sources DOAJ
author Lorentz Jäntschi
Claudia V. Cimpoiu
Elena M. Pică
Sorana D. Bolboacă
spellingShingle Lorentz Jäntschi
Claudia V. Cimpoiu
Elena M. Pică
Sorana D. Bolboacă
Statistical Assessment of Solvent Mixture Models Used for Separation of Biological Active Compounds
Molecules
Mathematical model
chromatographic response functions
statistical assessment
correlation.
author_facet Lorentz Jäntschi
Claudia V. Cimpoiu
Elena M. Pică
Sorana D. Bolboacă
author_sort Lorentz Jäntschi
title Statistical Assessment of Solvent Mixture Models Used for Separation of Biological Active Compounds
title_short Statistical Assessment of Solvent Mixture Models Used for Separation of Biological Active Compounds
title_full Statistical Assessment of Solvent Mixture Models Used for Separation of Biological Active Compounds
title_fullStr Statistical Assessment of Solvent Mixture Models Used for Separation of Biological Active Compounds
title_full_unstemmed Statistical Assessment of Solvent Mixture Models Used for Separation of Biological Active Compounds
title_sort statistical assessment of solvent mixture models used for separation of biological active compounds
publisher MDPI AG
series Molecules
issn 1420-3049
publishDate 2008-08-01
description Two mathematical models with seven and six parameters have been created for use as methods for identification of the optimum mobile phase in chromatographic separations. A series of chromatographic response functions were proposed and implemented in order to assess and validate the models. The assessment was performed on a set of androstane isomers. Pearson, Spearman, Kendall tau-a,b,c and Goodman-Kruskal correlation coefficients were used in order to identify and to quantify the link and its nature (quantitative, categorical, semi-quantitative, both quantitative and categorical) between experimental values and the values estimated by the mathematical models. The study revealed that the six parameter model is valid and reliable for five chromatographic response factors (retardation factor, retardation factor ordered ascending by the chromatographic peak, resolution of pairs of compound, resolution matrix of successive chromatographic peaks, and quality factor). Furthermore, the model could be used as an instrument in analysis of the quality of experimental data. The results obtained by applying the model with six parameters for deviations of rank sums suggest that the data of the experiment no. 8 are questionable.
topic Mathematical model
chromatographic response functions
statistical assessment
correlation.
url http://www.mdpi.com/1420-3049/13/8/1617/
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