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Advancements in continuous processing technologies in parallel with the expansion of complex organic reactions enabled by flow chemistry have led to the increasing use of flow reactions throughout the pharmaceutical industry. However, reaction development in flow is typically plagued by inefficiencies associated with collecting data under steady-state conditions and data-rich experimentation options for characterizing flow reactions remain sparse. In the early stages of drug development, this challenged is compounded by limited availability of key raw materials and short development timelines.
Automated transient/dynamic reaction experiments provide a viable process development intensification option to lessen the resource burden and inefficiencies surrounding flow reaction process development. Moreover, appropriate coupling of this technique with inline Process Analytical Technologies enables the generation of rich datasets during extended, unattended experiments, such as stability studies or integrated reaction self-optimization. In this presentation, Brian Wyvratt discusses examples of how Merck leverages automated flow systems to improve knowledge capture while limiting resource burdens.
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Brian M. Wyvratt
Associate Principal Scientist, Merck & Co., Inc
Brian is currently an Associate Principal Scientist in the Development Sciences and Clinical Supply organization within Merck Research Labs. Prior to Brian’s current role within the small molecule pilot plant, he supported late stage process development and commercialization for multiple projects. Brian has been actively involved in reactor automation, particularly for flow applications, to enable smart, efficient data-rich experimentation as well as feedback control. Prior to joining Merck in 2016, Brian obtained his BS degree from Lehigh University and PhD from the University of Michigan, both in Chemical Engineering.