Dynamic flow experiments for data-rich optimization
Jason D. Williams, Peter Sagmeister, C. Oliver Kappe
Abstract
Flow chemistry is having an increasing influence on manufacturing in the chemical industry, but significant barriers remain in the development of these continuous processes. Dynamic flow experiments have the potential to democratize and accelerate process development in a data-rich manner, reducing time and material wastage. Models based on the data gathered can also be leveraged to decrease waste in a manufacturing environment. Here, we summarize the literature reports of dynamic flow experiments (most of which are from the past 5 years), with a focus on: experiment design, process analytics, and utilization of the resulting data. Finally, an example of dynamic experiments in pharmaceutical development is discussed in detail. A higher uptake of dynamic experiments in industrial environments in the coming years will undoubtedly facilitate greener manufacturing processes.