Jennifer K. Field is a research scientist at Shimadzu Centre of Excellence.
Anomalous Retention Prediction Using Modelling Software in Gradient Reversed-Phase Liquid Chromatography: Why it Can Occur and How to Prevent It
The success of screening column and mobile phase combinations that generate dissimilar selectivity is highlighted in a typical method development strategy.
Method Development for Reversed-Phase Separations of Peptides: A Rational Screening Strategy for Column and Mobile Phase Combinations with Complementary Selectivity
This review article summarizes the results obtained from the combined efforts of a joint academic and industrial initiative to solve the real-life challenge of determining low levels of peptide-related impurities in the presence of the related biologically-active peptide at a high concentration.
Understanding How Dwell Volume Can Affect Selectivity in Reversed-Phase Gradient Chromatography
The effect of dwell volume on chromatographic selectivity can be successfully modelled using retention prediction software. Hence, the robustness of reversed-phase LC gradient methodologies, with respect to dwell volume, can be conveniently assessed.
A Practical Approach to Modelling of Reversed-Phase Liquid Chromatographic Separations: Advantages, Principles, and Possible Pitfalls
Chromatographic principles and best practices for obtaining highly precise retention time, peak width, and resolution predictions for the optimization of reversed-phase liquid chromatography (LC) separations using retention modelling software will be discussed. The importance of fully characterizing the LC instrumentation, how to generate accurate input data, the selection of appropriate models, and peak tracking will be addressed along with a suggested workflow. Adhesion to a few basic rules and simple precautions and the use of modern retention modelling software programmes can assist the rapid development of highly accurate retention models to enable the development of robust and optimized reversed-phase LC separations using either ultrahigh-pressure liquid chromatography (UHPLC) or high performance liquid chromatography (HPLC) conditions. Examples of retention modelling for small and large molecules will be highlighted.
Supplementary Appendix 2 to A Practical Approach to Modelling of Reversed-Phase Liquid Chromatographic Separations: Advantages, Principles, and Possible Pitfalls
Supplementary Appendix 1 to A Practical Approach to Modelling of Reversed-Phase Liquid Chromatographic Separations: Advantages, Principles, and Possible Pitfalls
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