Automated method development in high-pressure liquid chromatography.

Active learning Automation Modelling Separation optimization

Journal

Journal of chromatography. A
ISSN: 1873-3778
Titre abrégé: J Chromatogr A
Pays: Netherlands
ID NLM: 9318488

Informations de publication

Date de publication:
12 Dec 2023
Historique:
received: 24 11 2023
revised: 08 12 2023
accepted: 11 12 2023
medline: 18 12 2023
pubmed: 18 12 2023
entrez: 17 12 2023
Statut: aheadofprint

Résumé

Method development in liquid chromatography is a crucial step in the optimization of analytical separations for various applications. However, it is often a challenging endeavour due to its time-consuming, resource intensive and costly nature, which is further hampered by its complexity requiring highly skilled and experienced scientists. This review presents an examination of the methods that are required for a completely automated method development procedure in liquid chromatography, aimed at taking the human out of the decision loop. Some of the presented approaches have recently witnessed an important increase in interest as they offer the promise to facilitate, streamline and speed up the method development process. The review first discusses the mathematical description of the separation problem by means of multi-criteria optimization functions. Two different strategies to resolve this optimization are then presented; an experimental and a model-based approach. Additionally, methods for automated peak detection and peak tracking are reviewed, which, upon integration in an instrument, allow for a completely closed-loop method development process. For each of these approaches, various currently applied methods are presented, recent trends and approaches discussed, short-comings pointed out, and future prospects highlighted.

Identifiants

pubmed: 38104507
pii: S0021-9673(23)00802-6
doi: 10.1016/j.chroma.2023.464577
pii:
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

464577

Informations de copyright

Copyright © 2023 Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Emery Bosten (E)

Department for Pharmaceutical and Pharmacological Sciences, Pharmaceutical Analysis, University of Leuven (KU Leuven), Herestraat 49, Leuven 3000, Belgium; Department of Pharmaceutical Development and Manufacturing Sciences, Janssen Pharmaceutica, Turnhoutseweg 30, Beerse, Belgium.

Alexander Kensert (A)

Department for Pharmaceutical and Pharmacological Sciences, Pharmaceutical Analysis, University of Leuven (KU Leuven), Herestraat 49, Leuven 3000, Belgium.

Gert Desmet (G)

Department of Chemical Engineering, Free University of Brussels (VUB), Pleinlaan 2, Brussels 1050, Belgium.

Deirdre Cabooter (D)

Department for Pharmaceutical and Pharmacological Sciences, Pharmaceutical Analysis, University of Leuven (KU Leuven), Herestraat 49, Leuven 3000, Belgium. Electronic address: deirdre.cabooter@kuleuven.be.

Classifications MeSH