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Tanaka-parameter based approach for chromatographic column selection How to locate ‘k’ columns with the most dissimilar chromatographic selectivity from a selection of ‘n’ columns in a database
EP25978
Poster Title: Tanaka-parameter based approach for chromatographic column selection How to locate ‘k’ columns with the most dissimilar chromatographic selectivity from a selection of ‘n’ columns in a database
Submitted on 29 Jun 2017
Author(s): K. Kassam,1* D. Tsarev,1 and M. Euerby2
Affiliations: 1 Advanced Chemistry Development, Inc. (ACD/Labs), 8 King Street East, Suite 107, Toronto, ON., M5C 1B5. Canada 2 University of Strathclyde, Strathclyde Institute of Pharmacy and Biomedical Sciences, 161 Cathedral Street, Glasgow, G4 0RE, UK
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Poster Information
Abstract: A common approach to chromatographic method development is to screen different combinations of columns and mobile phases that are expected to give good retention, good peak shape, as well as large differences in selectivity. Subsequently, gradient and temperature are optimised for the most promising combination, often using retention modelling.[1]

The selection of columns to be included in a screen is not trivial. The best approach is probably to select a group of modern columns (i.e., n columns) that are expected to provide good stability, adequate retention, and good peak shape for the analytes in question, and thereafter select a subset (i.e., k columns, typically four or six columns) of these which provide large differences in selectivity for screening. Usually this is done by picking stationary phases with different ligands based on information from column manufacturers. However, two C18 columns can actually display larger differences in selectivity than a C18 column and a phenyl column.

Tanaka parameters [2] combined with weighted and scaled Euclidean distance between two multidimensional points, referred to as Column Distance Factor (CDF), have been successfully used to identify the degree of similarity of two columns. [3] This is useful for the identification of replacement/backup columns. It is less useful for the identification of the most diverse columns for screening. In this study, we will describe an approach that allows the selection of n columns of interest from the database and, subsequently, the identification of k columns among these with the most different selectivity by maximizing the CDF from any pair of columns.
Summary: A new approach to orthogonal column selection based on Tanaka parameters. Comparison to current practices and illustration of the success of the approach with an exampleReferences: 1. N. Tanaka et al. (1989). Chromatographic Characterization of
Silica C18 Packing Materials. Correlation between a Preparation
Method and Retention Behavior of Stationary Phase. J.
Chromatogr. Sci. 27: 721-728.
2. M.R. Euerby and P. Petersson. (2003). Chromatographic
classification and comparison of commercially available reversedphase
liquid chromatographic columns using principal component
analysis. J. Chromatogr. A. 994: 13-36.
3. www.acdlabs.com/columnselector
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