Scientific article
OA Policy
English

Chromatographic strategies for the analytical characterization of adeno-associated virus vector-based gene therapy products

Published inTrAC. Trends in analytical chemistry, vol. 164, 117088
Publication date2023-07
First online date2023-05-10
Abstract

In recent years, the biopharmaceutical industry's interest in gene therapy modalities has increased dramatically. To warrant their quality during manufacturing and upstream/downstream process, fit-for-purpose analytical methods play a crucial role in the overall control strategy. However, characterization of gene therapy products remains challenging due to their large size, structural complexity, heterogeneity, potential instability, and limited sample availability. In addressing some of these challenges with innovative approaches, liquid chromatography (LC) based methods have become an integral part of the currently used analytical toolbox. This review focuses on both established methods and emerging trends in the LC analysis of adeno-associated virus (AVV) vector-based gene therapy products. Each method is discussed to highlight their advantages, drawbacks, and unique capabilities in the analysis of AAV gene transfer vehicles and their corresponding impurities. Taken together, this review provides guidance on the selection of LC-based methods for routine testing and extended characterization of gene therapy products.

Keywords
  • Recombinant adeno-associated virus
  • Full capsid
  • Empty capsid
  • Viral proteins
  • Ion exchange chromatography
  • Reversed phase liquid chromatography
  • Hydrophilic interaction chromatography
  • Size exclusion chromatography
Research groups
Citation (ISO format)
FEKETE, Szabolcs et al. Chromatographic strategies for the analytical characterization of adeno-associated virus vector-based gene therapy products. In: TrAC. Trends in analytical chemistry, 2023, vol. 164, p. 117088. doi: 10.1016/j.trac.2023.117088
Main files (1)
Article (Published version)
Identifiers
Journal ISSN0165-9936
97views
647downloads

Technical informations

Creation06/07/2023 12:42:58
First validation14/08/2023 08:56:07
Update14/08/2023 08:56:07
Status update14/08/2023 08:56:07
Last indexation01/11/2024 05:47:38
All rights reserved by Archive ouverte UNIGE and the University of GenevaunigeBlack