Accelerate Process Development: Combining Data-Rich Experimentation and Modeling for Improved Reaction Understanding

Date: 12 October 2023

Time: 15:00 (BST), 16.00 (CEST), 10.00 (EDT), 7.00 (PDT)

This webinar will feature two presentations and is aimed at chemists and chemical engineers who are interested in obtaining a deeper understanding of their processes at every scale to deliver increasingly complex processes under compressed timelines.

Flow Chemistry as a Tool in Reaction Mechanism Elucidation
Dr Tom Corrie, Syngenta

Mechanistic studies on chemical reactions are fundamental in the design of the optimal process. By truly understanding the processes we run, we can identify the strengths and limitations of the chemistry and perform targeted experimentation. However, depending on the complexity of the reaction, mechanistic studies can be lengthy and challenging to perform with high throughput. The aim of this talk is to demonstrate how flow chemistry can be used as a tool to accelerate mechanistic understanding through high quality data generation, automation, and adopting tools learnt through a successful collaboration with the University of Southampton.

Kinetic Analysis of Complex Organic Transformations; Democratizing PAT to Enable Kinetic Analysis and Modeling
Dr James Murray, Amgen

Standardizing kinetic analysis across our late stage portfolio has enabled efficient process optimization and characterization via improved mechanistic understanding. A key contributor to the success of this approach has been to deploy process analytical technologies (PAT) for in-situ reaction monitoring to collect continuous time course data throughout the course of each chemical reaction. We have automated reaction monitoring and kinetic analysis through implementation of a templated approach based on Reaction Progress Kinetic Analysis (RPKA). This has facilitated the collection of continuous kinetic data by scientists across a range of experience levels and allowed detailed mechanistic analysis for use in predictive kinetic modeling.

This webinar is sponsored by Mettler-Toledo and will take place at the following time:

15.00   BST (UK, Lisbon)
16.00   CEST (Paris, Madrid, Frankfurt etc)
10.00   EDT (New York, Boston)
7.00     PDT (San Francisco, LA)

If you are unable to attend on the day, do not worry, all registrants will be sent links to the recorded session and slides presented afterwards. Registrants who attend the ‘live’ session will receive an e-Certificate of Attendance.


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