A Slug Flow Platform with Multiple Process Analytics Facilitates Flexible Reaction Optimization

Abstract Flow processing offers many opportunities to optimize reactions in a rapid and automated manner, yet often requires relatively large quantities of input materials. To combat this, the use of a flexible slug flow reactor, equipped with two analytical instruments, for low‐volume optimization...

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Bibliographic Details
Main Authors: Florian Wagner, Peter Sagmeister, Clemens E. Jusner, Thomas G. Tampone, Vidhyadhar Manee, Frederic G. Buono, Jason D. Williams, C. Oliver Kappe
Format: Article
Language:English
Published: Wiley 2024-04-01
Series:Advanced Science
Subjects:
Online Access:https://doi.org/10.1002/advs.202308034
Description
Summary:Abstract Flow processing offers many opportunities to optimize reactions in a rapid and automated manner, yet often requires relatively large quantities of input materials. To combat this, the use of a flexible slug flow reactor, equipped with two analytical instruments, for low‐volume optimization experiments are reported. A Buchwald–Hartwig amination toward the drug olanzapine, with 6 independent optimizable variables, is optimized using three different automated approaches: self‐optimization, design of experiments, and kinetic modeling. These approaches are complementary and provide differing information on the reaction: pareto optimal operating points, response surface models, and mechanistic models, respectively. The results are achieved using <10% of the material that would be required for standard flow operation. Finally, a chemometric model is built utilizing automated data handling and three subsequent validation experiments demonstrate good agreement between the slug flow reactor and a standard (larger scale) flow reactor.
ISSN:2198-3844