Literature DB >> 28208251

Rapid Method Development in Hydrophilic Interaction Liquid Chromatography for Pharmaceutical Analysis Using a Combination of Quantitative Structure-Retention Relationships and Design of Experiments.

Maryam Taraji1, Paul R Haddad1, Ruth I J Amos1, Mohammad Talebi1, Roman Szucs2, John W Dolan3, Chris A Pohl4.   

Abstract

A design-of-experiment (DoE) model was developed, able to describe the retention times of a mixture of pharmaceutical compounds in hydrophilic interaction liquid chromatography (HILIC) under all possible combinations of acetonitrile content, salt concentration, and mobile-phase pH with R2 > 0.95. Further, a quantitative structure-retention relationship (QSRR) model was developed to predict retention times for new analytes, based only on their chemical structures, with a root-mean-square error of prediction (RMSEP) as low as 0.81%. A compound classification based on the concept of similarity was applied prior to QSRR modeling. Finally, we utilized a combined QSRR-DoE approach to propose an optimal design space in a quality-by-design (QbD) workflow to facilitate the HILIC method development. The mathematical QSRR-DoE model was shown to be highly predictive when applied to an independent test set of unseen compounds in unseen conditions with a RMSEP value of 5.83%. The QSRR-DoE computed retention time of pharmaceutical test analytes and subsequently calculated separation selectivity was used to optimize the chromatographic conditions for efficient separation of targets. A Monte Carlo simulation was performed to evaluate the risk of uncertainty in the model's prediction, and to define the design space where the desired quality criterion was met. Experimental realization of peak selectivity between targets under the selected optimal working conditions confirmed the theoretical predictions. These results demonstrate how discovery of optimal conditions for the separation of new analytes can be accelerated by the use of appropriate theoretical tools.

Entities:  

Mesh:

Substances:

Year:  2017        PMID: 28208251     DOI: 10.1021/acs.analchem.6b04282

Source DB:  PubMed          Journal:  Anal Chem        ISSN: 0003-2700            Impact factor:   6.986


  4 in total

Review 1.  A review of the pharmaceutical exposome in aquatic fauna.

Authors:  Thomas H Miller; Nicolas R Bury; Stewart F Owen; James I MacRae; Leon P Barron
Journal:  Environ Pollut       Date:  2018-04-10       Impact factor: 8.071

2.  Structure Driven Prediction of Chromatographic Retention Times: Applications to Pharmaceutical Analysis.

Authors:  Roman Szucs; Roland Brown; Claudio Brunelli; James C Heaton; Jasna Hradski
Journal:  Int J Mol Sci       Date:  2021-04-08       Impact factor: 5.923

3.  A pharmaceutical-related molecules dataset for reversed-phase chromatography retention time prediction built on combining pH and gradient time conditions.

Authors:  Thomas Van Laethem; Priyanka Kumari; Philippe Hubert; Marianne Fillet; Pierre-Yves Sacré; Cédric Hubert
Journal:  Data Brief       Date:  2022-03-04

4.  Mechanistic Chromatographic Column Characterization for the Analysis of Flavonoids Using Quantitative Structure-Retention Relationships Based on Density Functional Theory.

Authors:  Bogusław Buszewski; Petar Žuvela; Gulyaim Sagandykova; Justyna Walczak-Skierska; Paweł Pomastowski; Jonathan David; Ming Wah Wong
Journal:  Int J Mol Sci       Date:  2020-03-17       Impact factor: 5.923

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.