How to Use Data Analytics for Accelerating Vaccine Development
In this webinar, we will cover techniques in data analytics for accelerating vaccine discovery and development. These techniques are designed to surface trends and actionable insights across a wide range of data sets to alleviate the burden researchers and developers face as they look for clues that will speed up vaccine development and identify effective treatments.
Relevant methods and use-cases covered in this webinar include:
- MODDE® and Design of Experiments (DOE)
- SIMCA® and Multivariate Data Analysis (MVDA)
This Webinar is aimed at those working in R&D as well as leaders responsible for looking for ways to accelerate vaccine discovery and development.
Key Learning Objectives
- Vaccine discovery and development can be accelerated using various data analytics tools.
- MODDE DOE is a useful tool allowing users to understand the basics of experimental design and to achieve statistically optimal results from your experiments.
- SIMCA MVDA is a flexible tool which extracts information from large data sets allowing users to gain more in-depth process understanding and ultimately improve the quality, safety and efficacy of a drug product.
- MVDA and DOE are needed to accomplish QbD in Biopharma, in that they provide the necessary framework and guidance for a risk‐based approach to drug development through better process understanding and control.
Meet Our Experts
Market Manager (Bio)pharma
Tiffany McLeod is the Biopharma Market Manager within the Sartorius Stedim Data Analytics marketing team. She has been employed by Sartorius since 2017. Within this function Tiffany acts as the teams’ subject matter expert for biopharma market trends and requirements. She also works to addresses and develop data analytics solutions to solve industry challenges and pain points. She is passionate about biopharma 4.0 and helping businesses pursue digital transformations. Tiffany holds a degree in Bioengineering and Bioinformatics from the University of California, San Diego.
Senior Lecturer and Principal Data Scientist
Lennart Eriksson is a senior lecturer and data scientist and has worked with advanced data analytics for over three decades. Currently, he holds a position within the marketing team of Sartorius Stedim Data Analytics. His responsibilities relate to trainings, webinars, blogs and other marketing communications. Lennart has a PhD in Chemometrics and holds an associate professorship in Chemometrics at Umeå University. He has authored and co-authored over 100 publications on the applicability of design of experiments and multivariate data analysis in research, development and production. Lennart is a member of the editorial board of Journal of Chemometrics.