Concepts and optimization strategies of experimental design in continuous-flow processing

Abstract

The integration of flow systems with statistical design of experiments is emerging as a valuable strategy to develop new synthetic routes towards relevant building blocks, chemical probes, and drug compounds. Optimization by experimental design incorporates statistical algorithms, mathematical models and equations, predicting tools, feedback control, and validation to generate new optimal conditions. Continuous-flow chemistry is ideally suited for this scope, as the integration of in-line analysis is simple; experimental parameters such as temperature, pressure, and flow rate can be easily controlled and fine-regulated; and automation of reaction screening can be accomplished with software assistance. This review article aims to illustrate how the combination of flow synthesizers and design of experiments can be profitable to speed up the development and optimization of more efficient, safer, and reproducible protocols for modern synthetic methods and manufacturing processes.