fr
Article scientifique
Accès libre
Anglais

Expediting the chromatographic analysis of COVID-19 antibody therapeutics with ultra-short columns, retention modeling and automated method development

Date de publication2022-11
Résumé

The COVID-19 pandemic necessitated the emergency use authorization (EUA) of several new therapeutics and vaccines. Several monoclonal antibodies (mAbs) were among those authorized for use, and they have served a purpose to provide passive immunity and to help minimize dangerous secondary effects in at-risk and hospitalized patients infected with SARS-CoV-2. With an EUA submission, scientific data on a drug candidate is often collected near simultaneously alongside drug development. In such a situation, there is little time to allow misguided method development nor time to wait on traditional turnaround times. We have taken this dilemma as a chance to propose new means to expediting the chromatographic characterization of protein therapeutics. To this end, we have combined the use of automated, systematic modeling and ultrashort LC columns to quickly optimize high throughput RP, IEX, HILIC and SEC separations for two COVID-19-related mAbs. The development and verification of these four complementary analytical methods required only 2 days of experimental work. In the end, one chromatographic analysis can be performed with a sub-2 min run time such that it is feasible to comprehensively characterize a COVID-19 mAb cocktail by 4 different profiling techniques within a 1-hour turnaround time.

eng
Mots-clés
  • Automation
  • Casirivimab
  • Covid-19
  • Imdevimab
  • Retention modeling
  • Ultra-short column
Groupe de recherche
Citation (format ISO)
DUIVELSHOF, Bastiaan et al. Expediting the chromatographic analysis of COVID-19 antibody therapeutics with ultra-short columns, retention modeling and automated method development. In: Journal of pharmaceutical and biomedical analysis, 2022, vol. 221, p. 115039. doi: 10.1016/j.jpba.2022.115039
Fichiers principaux (1)
Article (Published version)
Identifiants
ISSN du journal0731-7085
112vues
46téléchargements

Informations techniques

Création18.10.2022 13:25:00
Première validation18.10.2022 13:25:00
Heure de mise à jour16.03.2023 09:02:50
Changement de statut16.03.2023 09:02:50
Dernière indexation17.01.2024 22:18:25
All rights reserved by Archive ouverte UNIGE and the University of GenevaunigeBlack