QbD and Process Characterization

Duration: 60 minutes


Registration

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Why watch

Summary

Product quality is achieved through process validation. During process characterization, manufacturers are using Quality By Design tools in order to acquire knowledge on the process. In this webinar, process scientists will be introduced to important concepts that will ease their communication with statisticians. 

Key Learnings

  •  Design of Experiments is the most efficient tool to explore multivariate relationship between Process Parameters
  •  Design Space is the multivariate area of Process Parameters ensuring a high probability of success to meet the specifications for Critical Quality Attributes
  •  Computing and reporting Design Space are essential parts of the Quality by Design approach
speakers

A full day of inspirational speakers

Proud to bring inspirational speakers from across the globe. 


 

 

 


 

 

Jean-Francois Michiels

Senior Manager Statistic, PharmaLex

Jean-François Michiels has a bioengineering degree from the Université Catholique de Louvain (Belgium-2003). He began a PhD thesis in animal cell culture (2004-2011-UCL-Belgium), entitled “Investigation of the role of peptones in animal cell culture: case study of a commercial soy”. In 2013, he was intern in statistics and afterwards had the opportunity to work on various statistical projects. His knowledge covers bioassay and process development, the use of Design of experiments and of linear, multivariate and mixed model regression. He is also providing support for Adaptive design for clinical trials. R, JMP and SAS are used as the main statistical software.

 

Angel (Yuelin) Lu

Manager, PharmaLex

Angel (Yuelin) Lu has a Ph.D. in statistics from Baylor University (2019 US). Her thesis involved modeling vaccine efficacy for selection bias samples and prediction of survival probability in prime-boost vaccination regime, both using Bayesian methods. She joined PharmaLex in 2017 and has worked on various non-clinical projects focusing on design of experiments, manufacturing, and bioassay development. In particular, she has significant experience using Bayesian methodologies in non-clinical applications, as well as with linear mixed models. Her clients include several of the largest pharmaceutical companies, and her work has taken her to client sites in the United States, Europe and China.