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

Area of Science:

• Chemical Engineering
• Process Chemistry
• Analytical Chemistry

Background:

• Flow processing enables rapid, automated reaction optimization but typically demands substantial material quantities.
• Developing low-volume methods is crucial for efficient optimization, especially for high-value compounds.

Purpose of the Study:

• To report the optimization of low-volume experiments using a flexible slug flow reactor.
• To compare three automated optimization strategies: self-optimization, design of experiments, and kinetic modeling.
• To validate the slug flow reactor's performance against standard flow reactors.

Main Methods:

• Utilized a flexible slug flow reactor with integrated analytical instruments.
• Employed self-optimization, design of experiments, and kinetic modeling for reaction optimization.
• Optimized a Buchwald-Hartwig amination for olanzapine synthesis with six variables.

Main Results:

• Achieved reaction optimization using less than 10% of the material required for standard flow operations.
• Generated complementary data: Pareto optimal points, response surface models, and mechanistic models.
• Developed a chemometric model and validated it with three experiments, showing good agreement with a larger-scale flow reactor.

Conclusions:

• Low-volume slug flow reactors are effective for optimizing complex reactions with minimal material.
• Automated optimization strategies provide diverse and valuable insights into reaction parameters.
• The developed slug flow system offers a viable and efficient alternative to traditional flow reactors for process optimization.