Ever-more structurally complex bio-molecules and biological entities coming in focus of pharma development warrant growing requirements for fit-for-purpose analytics and extended 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.
Summary
- Date:
- May 18 2020 - May 18 2020
- Time:
-
10:30 - 11:30
(GMT-05:00) Eastern [US & Canada] - Event type:
- Webinar - Live
- Language:
- English
- Technology:
-
Dynamic Light Scattering
Differential Scanning Calorimetry (DSC) - Industry:
-
Pharmaceuticals
Biosciences
Speakers
John Stenson Ph.D. - Product Manager - Nanomaterials - Malvern Panalytical
Natalia Markova Ph.D. - Application Specialist DSC - Malvern Panalytical
More information
- Who should attend?
- What will you learn?
- How this unique offering of detectors from Malvern Panalytical can be synergistically used to more fully describe rAAV attributes.