A comprehensive study on adeno-associated virus analysis using a 3 μm monodisperse size exclusion chromatography column

Adeno-associated viruses (AAVs) are as small, replication-defective, non-enveloped viruses, serving as vectors for gene therapy. AAV vectors play a transformative role in delivering therapeutic genes with low immunogenicity, safety, and long-term transient expression. In AAV production, the separation of monomeric forms from aggregates is pivotal for optimal gene therapy outcomes. The success of AAV-based gene therapies relies on the purity and homogeneity of AAV vector populations, necessitating the monitoring of AAV aggregation for production and quality assurance.

 

Size-exclusion liquid chromatography (SEC) has been the preferred method for detecting and quantifying AAV aggregates. SEC is a non-interacting, passive separation chromatographic technique utilizing differential exclusion sample components based on size to effectively separate monomeric AAV particles from their associated aggregates. Advantages of SEC chromatographic methods include straightforward development, high sample throughput, and complementarity with techniques such as ELISA, cryogenic electron microscopy (cryo-EM), and AUC.

 

Our study details an effective approach for separating AAV monomeric capsids from high molecular weight species (HMWS) using a SEC column packed with 550 Å pore size, 3μm monodisperse silica particles in hydrophilic-coated stainless-steel hardware. The monodispersed silica particles feature a proprietary diol hydrophilic layer, ensuring an extremely low level of undesired interaction sites. Compared to traditional polydisperse particles, the monodisperse particles exhibit a consistent size distribution. This characteristic enables precise control during media synthesis and column packing, leading to substantial enhancements in column-to-column and lot-to-lot reproducibility. The SEC column housed in state-of-the-art hydrophilic-coated stainless-steel hardware aims to eliminate secondary interactions, ensuring optimal performance during the initial injection process.

 

Learning Objectives