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Overcoming Challenges with AAV Aggregate Analysis Using a Novel SEC Column to Determine Critical...

Автор: Labroots

Загружено: 2024-12-31

Просмотров: 80

Описание: Presented By: Shilin Cheung, Ph.D.
Speaker Biography:
Dr. Cheung received her BS (2006) and Ph.D. (2012) in Bioanalytical Chemistry from the University of Toronto. She has developed, qualified, and validated innovative analytical methods in CE based microfluidics, automated low volume UV-vis spectroscopy, and UHPLC assays. Her methods have been applied to manufacturing process developments, formulation and stability and DS/DP characterization and specification testing. At Phenomenex she is focused on developing fit for purpose analytical methods to help advance developments in gene therapeutics.

Webinar: Overcoming Challenges with AAV Aggregate Analysis Using a Novel SEC Column to Determine Critical Quality Attributes
Webinar Abstract:
As the most widely used viral vector for gene therapies, Adeno-Associated Viruses (AAVs) present unique advantages, including their ability to enter both dividing and non-dividing cells, the absence of human viral illness, and minimal immune response triggers.

However, the complexity and size of AAVs pose challenges for their analysis. Traditional approaches struggle with their larger size, hindering comprehensive characterization crucial for ensuring the safety, efficacy, and functionality of gene therapies. This is particularly true for aggregate analysis testing which is a critical quality attribute (CQA) and accompanies other challenges including long run times, high sample consumption where sample quantities are limited, and accurate quantitation of monomer and aggregate species.

In this webinar, Sr. Research Scientist Shilin Cheung, will review optimization of high throughput size exclusion chromatography methods using a novel 700 Å pore size SEC chemistry to reduce sample consumption and run times. Additionally, method versatility with multiple mobile phase conditions utilizing various detectors across several AAV serotypes will be explored.

Learning Objectives
Learn how a novel 700 Å pore size SEC chemistry improves lab throughput and reduces sample consumption for AAV aggregate analysis
Review of method optimization best practices to maximize AAV monomer/aggregate resolution
Learn how selecting appropriate particle chemistry, pore size and hardware improves SEC performance for AAV analysis

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