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Derringer desirability and kinetic plot LC-column comparison approach for MS-compatible lipopeptide analysis 被引量:1
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作者 Matthias D’Hondt Frederick Verbeke +3 位作者 Sofie Stalmans Bert Gevaert Evelien Wynendaele Bart De Spiegeleer 《Journal of Pharmaceutical Analysis》 SCIE CAS 2014年第3期173-182,共10页
Lipopeptides are currently re-emerging as an interesting subgroup in the peptide research field, having historical applications as antibacterial and antifungal agents and new potential applications as antiviral, antit... Lipopeptides are currently re-emerging as an interesting subgroup in the peptide research field, having historical applications as antibacterial and antifungal agents and new potential applications as antiviral, antitumor, immune-modulating and cell-penetrating compounds. However, due to their specific structure, chromatographic analysis often requires special buffer systems or the use of trifluoroacetic acid, limiting mass spectrometry detection. Therefore, we used a traditional aqueous/acetonitrile based gradient system, containing 0.1% (m/v) formic acid, to separate four pharmaceutically relevant lipopeptides (polymyxin B1, caspofungin, daptomycin and gramicidin A1), which were selected based upon hierarchical cluster analysis (HCA) and principal component analysis (PCA).In total, the performance of four different C18 columns, including one UPLC column, were evaluated using two parallel approaches. First, a Derringer desirability function was used, whereby six single and multiple chromatographic response values were rescaled into one overall D-value per column. Using this approach, the YMC Pack Pro C18 column was ranked as the best column for general MS-compatible lipopeptide separation. Secondly, the kinetic plot approach was used to compare the different columns at different flow rate ranges. As the optimal kinetic column performance is obtained at its maximal pressure, the length elongation factor λ(Pmax/Pexp) was used to transform the obtained experimental data (retention times and peak capacities) and construct kinetic performance limit (KPL) curves, allowing a direct visual and unbiased comparison of the selected columns, whereby the YMC Triart C18 UPLC and ACE C18 columns performed as best. Finally, differences in column performance and the (dis)advantages of both approaches are discussed. 展开更多
关键词 LIPOPEPTIDE Hierarchical cluster analysis (HCA) Principal component analysis (PCA) LC-MS kinetic plot Derringer desirability function
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Kinetic performance comparison of fully and superfcially porous particles with sizes ranging between 2.7 lm and 5 lm: Intrinsic evaluation and application to a pharmaceutical test compound 被引量:2
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作者 K.Broeckhoven D.Cabooter G.Desmet 《Journal of Pharmaceutical Analysis》 SCIE CAS 2013年第5期313-323,共11页
The reintroduction of superficially porous particles has resulted in a leap forward for the separation performance in liquid chromatography. The underlying reasons for the higher efficiency of columns packed with thes... The reintroduction of superficially porous particles has resulted in a leap forward for the separation performance in liquid chromatography. The underlying reasons for the higher efficiency of columns packed with these particles are discussed. The performance of the newly introduced 5 p.m superficially porous particles is evaluated and compared to 2.7 pm superficially porous and 3.5 and 5 p.m fully porous columns using typical test compounds (alkylphenones) and a relevant pharmaceutical compound (impurity of amoxicillin). The 5 I.tm superficially porous particles provide a superior kinetic performance compared to both the 3.5 and 5 Ixm fully porous particles over the entire relevant range of separation conditions. The performance of the superficially porous particles, however, appears to depend strongly on retention and analyte properties, emphasizing the importance of comparing different columns under realistic conditions (high enough k) and using the compound of interest. 展开更多
关键词 kinetic plot Superfcially porous particles 5 μm Permeability Amoxicillin impurity Alkylphenones
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