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

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, we report the use of a flexible droplet flow reactor, equipped with two analytical instruments, for low-volume optimization experiments. A Buchwald-Hartwig amination toward the drug olanzapine, with 6 independent optimizable variables, was 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 were achieved using <10% of the material that would be required for standard flow operation. Finally, a chemometric model was built utilizing automated data handling and three subsequent validation experiments demonstrated good agreement between the droplet flow reactor and a standard (larger scale) flow reactor.