Accurate prediction of retention in hydrophilic interaction chromatography by back calculation of high pressure liquid chromatography gradient profiles.

J Chromatogr A

Department of Plant and Microbial Biology, University of Minnesota, 1479 Gortner Ave., St. Paul, MN 55108, USA.

Published: October 2017

Gradient retention times are difficult to project from the underlying retention factor (k) vs. solvent composition (φ) relationships. A major reason for this difficulty is that gradients produced by HPLC pumps are imperfect - gradient delay, gradient dispersion, and solvent mis-proportioning are all difficult to account for in calculations. However, we recently showed that a gradient "back-calculation" methodology can measure these imperfections and take them into account. In RPLC, when the back-calculation methodology was used, error in projected gradient retention times is as low as could be expected based on repeatability in the k vs. φ relationships. HILIC, however, presents a new challenge: the selectivity of HILIC columns drift strongly over time. Retention is repeatable in short time, but selectivity frequently drifts over the course of weeks. In this study, we set out to understand if the issue of selectivity drift can be avoid by doing our experiments quickly, and if there any other factors that make it difficult to predict gradient retention times from isocratic k vs. φ relationships when gradient imperfections are taken into account with the back-calculation methodology. While in past reports, the accuracy of retention projections was >5%, the back-calculation methodology brought our error down to ∼1%. This result was 6-43 times more accurate than projections made using ideal gradients and 3-5 times more accurate than the same retention projections made using offset gradients (i.e., gradients that only took gradient delay into account). Still, the error remained higher in our HILIC projections than in RPLC. Based on the shape of the back-calculated gradients, we suspect the higher error is a result of prominent gradient distortion caused by strong, preferential water uptake from the mobile phase into the stationary phase during the gradient - a factor our model did not properly take into account. It appears that, at least with the stationary phase we used, column distortion is an important factor to take into account in retention projection in HILIC that is not usually important in RPLC.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5623078PMC
http://dx.doi.org/10.1016/j.chroma.2017.08.050DOI Listing

Publication Analysis

Top Keywords

gradient retention
12
retention times
12
back-calculation methodology
12
gradient
11
retention
9
gradient delay
8
imperfections account
8
retention projections
8
times accurate
8
stationary phase
8

Similar Publications

In silico optimization of a challenging bispecific antibody chromatography step.

Biotechnol Prog

January 2025

Automation, Digital and Learning Solutions, Cytiva, Karlsruhe, Germany.

Mechanistic modeling of chromatographic steps is an effective tool in biopharma process development that enhances process understanding and accelerates optimization efforts and subsequent risk assessment. A relatively new model for ion exchange chromatography is the colloidal particle adsorption (CPA) formalism, which promises improved separation of material and molecule-specific parameters. This case study demonstrates a straightforward CPA modeling workflow to describe an ion exchange chromatography polishing step of a knobs-into-holes construct bispecific antibody molecule.

View Article and Find Full Text PDF

We introduce here a novel approach, termed time-segmented acquisition (Seg), to enhance the identification of peptides and proteins in trapped ion mobility spectrometry (TIMS)-time-of-flight (TOF) mass spectrometry. Our method exploits the positive correlation between ion mobility values and reversed-phase liquid chromatography (LC) retention time to improve ion separation and resolution. By dividing the LC retention time into multiple segments and applying a segment-specific narrower ion mobility range within the TIMS tunnel, we achieved better separation and higher resolution of ion mobility.

View Article and Find Full Text PDF

Global retention model based on multisample system parameters for optimising chromatographic fingerprints of medicinal plants.

Anal Chim Acta

February 2025

Department of Analytical Chemistry, Faculty of Chemistry, Universitat de València, C/ Dr. Moliner 50, 46100, Burjassot, Spain. Electronic address:

Background: Developing analytical methods for Traditional Medicine products by liquid chromatography is challenging due to their chemical complexity and the lack of analytical standards for numerous, unidentified constituents. Regulatory agencies recommend chromatographic fingerprint analysis for quality evaluation, relying on peak detection to ensure resolution. Conventional modelling struggles to optimise experimental conditions for such complex samples.

View Article and Find Full Text PDF

Interpretable machine learning reveals transport of aged microplastics in porous media: Multiple factors co-effect.

Water Res

January 2025

School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China; Key Laboratory of Coastal Zone Exploitation and Protection, Ministry of Natural Resources, Nanjing 210024, China. Electronic address:

Microplastics (MPs) easily migrate into deeper soil layers, posing potential risks to subterranean habitats and groundwater. However, the mechanisms governing the vertical migration of MPs in soil, particularly aged MPs, remain unclear. In this study, we investigate the transport of MPs under varying MPs properties, soil texture and hydrology conditions.

View Article and Find Full Text PDF

Radix Rehmanniae (RR) is a widely used herb in traditional Chinese Medicine with properties of tonifying the kidneys and nourishing the blood. Both raw and processed RR are effective for the treatment of diabetes in clinical practice. Oligosaccharides and iridoid glycosides are the primary active components responsible for the anti-diabetic effects of RR.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!