Improved control on process robustness by implementing predictive modelling utilizing novel design of experiments data

Currently process development and characterization in biopharmaceutical development should be performed according to the concept of Quality by Design (QbD) as outlined in the FDA imperative. The focus of QbD is that the quality should be built into a product with emphasis on product understanding, process understanding and process control. For process understanding and process control the relation between the critical process parameters and the critical quality attributes needs to be established. DoE proves to be a useful method to obtain this link, significantly reducing the amount of time consuming experiments.

At Batavia Biosciences we use DoE in pharmaceutical development. For example, we use DoE to identify parameters that affect the virus inactivation rate and yield. Furthermore, DoE is used for the initial screening of multiple parameters to define the critical parameters that affect the critical quality attributes (CQA’s). We will translate these parameters in a statistical model to explain the different inactivation rates and we will step into defining the operational parameter ranges to obtain the required quality (design space) and the optimal settings within the design space for quality, process performance and robustness. Finally, we will show how DoE is used for verification of the process or robustness testing.

In this webinar you will learn how to use DoE in planning your experiments and analyzing the data obtained. We will guide you through all phases of a DoE workflow and show you how Batavia Biosciences uses it to optimize USP and DSP development. So if you are interested in accelerating your biopharmaceutical processes and optimizing your development, please register.