Using zeta potential for the surface characterization of viral and lipid-based vectors

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Vectors Analytics Masterclass 3/6

Zeta potential (surface charge) characterization of viral and lipid-based vectors is a key attribute in the development of next-generation vaccines and other advanced pharmaceutical products. This information can be used to improve product design, optimize production processes, and determine stability and release specifications of the final product.

In this webinar, we will discuss how zeta potential characterization of viral and lipid-based vectors can be used to study different formulations and help predict their stability and fate in vivo. In addition, we will also be looking at the importance of pH titrations in understanding how changes in dispersant conditions could influence formulation stability.

Vector Analytics Masterclass:

This is the third in our “Vector Analytics Masterclass” series of webinars. Join us as our team of in-house characterization experts dive deep into the methodologies you need for successful vector development. They’ll also show you how to generate robust measurements and help you understand how a holistic approach to generating data analysis will give you greater confidence in your results.

Palestrante

  • Mike Kaszuba - Technical Support Manager and subject matter expert

Mais informações

Who should attend:

Scientists and project leaders working on the design, process and formulation development of viral and non-viral delivery vectors, such as viral particles, lipid nanoparticles (LNPs) and liposomes for drug and vaccine delivery.

What will you learn:

  • Understanding of the analytical technologies available for LNP vector characterization and what the techniques can tell you about your sample

  • Learn how to analyze specific characteristics of lipid nanoparticles

  • Understand the importance of applying orthogonal techniques

  • Understand the strengths and weaknesses of various characterization techniques for the development of LNPs as drug delivery vectors