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Molecules 2008, 13(8), 1617-1639; doi:10.3390/molecules13081617

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

1
“Iuliu Haţieganu” University of Medicine and Pharmacy Cluj-Napoca, Department of Medical Informatics and Biostatistics, 6 Louis Pasteur, 400349 Cluj-Napoca, Romania.
2
Technical University of Cluj-Napoca, 103-105 Muncii Bvd, 400641 Cluj-Napoca, Romania
3
“Babeş-Bolyai” University, Department of Analytical Chemistry, 11 Arany Janos, 400028 Cluj-Napoca, Romania
*
Author to whom correspondence should be addressed.
Received: 23 May 2008 / Revised: 7 August 2008 / Accepted: 7 August 2008 / Published: 11 August 2008
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Abstract

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.
Keywords: Mathematical model; chromatographic response functions; statistical assessment; correlation. Mathematical model; chromatographic response functions; statistical assessment; correlation.
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Bolboacă, S.D.; Pică, E.M.; Cimpoiu, C.V.; Jäntschi, L. Statistical Assessment of Solvent Mixture Models Used for Separation of Biological Active Compounds. Molecules 2008, 13, 1617-1639.

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