Delving Deeper Into AAV Attributes: Enhanced Characterization Using Multiple Technologies

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Ever-more structurally complex bio-molecules and biological entities are coming into focus within the pharma development space warranting growing requirements for fit-for-purpose analytics and extendeding characterization through orthogonal use of multiple technologies.

Viruses have long been used in vaccine development as delivery vehicles or attenuated and inactivated vaccines. They are also increasingly used as vectors in gene therapy. Recombinant Adeno-Associated Viruses (rAAV) are a class of viral vector that is being investigated intensively in the development of gene therapies. In order to develop efficient rAAV therapies produced through controlled and economical manufacturing processes, multiple challenges need to be addressed starting from capsid design through identification of optimal process and formulation conditions to comprehensive quality control of Drug Substance and Drug Product.

Addressing these challenges require extensive characterization of rAAV samples with multiple assays including measurements of capsid count, % full rAAV particles, particle size, aggregate formation, stability, genome release and capsid charge.

In this webinar, Natalia Markova and John Stenson of Malvern Panalytical will present on how Dynamic Light Scattering, Differential Scanning Calorimetry and multi-detection SEC (SEC-MALS) can be used as orthogonal and complementary technologies for enhanced characterization and generation of multi-parametral stability profile of rAAV samples.

演讲嘉宾

John Stenson Ph.D. - Product Manager - Nanomaterials - Malvern Panalytical 
Natalia Markova Ph.D. - Application Specialist DSC - Malvern Panalytical

更多信息

  • Who should attend?
- Scientist working on development of viral vector gene Therapies and viral vaccines.


  • What will you learn?
- How DLS, multi-detection SEC (SEC-MALS) and DSC can inform on analytical attributes and multiple stability metrics of rAAV. 

- How this unique offering of detectors from Malvern Panalytical can be synergistically used to more fully describe rAAV attributes.