Location: Webinar - Virtual
Start Date: May 16, 2024
Start Time: 05:00 CET | 20:00 PST | 23:00 EST | 04:00 BST
Type of Event: Webinars

This webinar has since taken place. It is now available to watch on-demand

About the Webinar

As part 3 in our webinar series, "Mastering Quality By Design", this webinar will focus on the application of Design of Experiment (DoE) to chemical reactions. Despite a high resistance to use statistical tools in chemistry, the DoE can have many advantages when compared to the “one factor at time” strategy, reducing the quantity of reactions and identifying the interactions between factors with the definition of the optimal conditions.

Attendees will learn how the DoE can be applied to chemical reactions and how a DoE can be planned, identifying the factors that can affect the outputs. Additionally, case studies related to API development will be presented to show the real advantages of the DoE.

Meet Our Speaker

Francesco Tinazzi ORG
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Francesco Tinazzi

Research Expert, API Development

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Latest update: May 2024

Biography


Francesco, a chemistry graduate from the University of Padova (Italy) in 1991, embarked on his career at Glaxo in Verona in 1992. Initially part of the Chemical Development Department, he honed his expertise in lab-scale chemistry and scale-up challenges. Later, as a member of the Lab Automation Team since 1997, Francesco developed and utilized automated systems for multiple and parallel reactions, enabling rapid optimization and deeper understanding of chemical processes. His profound knowledge of Quality by Design (QbD) principles and statistical tools, including principal component analysis (PCA), multivariate analysis (MVA), and experimental designs (DoE), seamlessly integrates with automated workstations for solvent/reagent screenings and process optimization. Currently, at Evotec Verona’s API Development and Manufacturing Department, Francesco oversees chemical projects from conception to pilot plant technology transfer, ensuring a smooth progression from route definition to reaction optimization.

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