Modernizing Process Chemistry for Efficiency and Robustness

Abstract

Process chemistry evolves through the increasing integration of automation, real-time analytics, and predictive modelling into development workflows. In pharmaceutical process development, these tools provide an opportunity to move beyond empirical optimization toward a more informed and scalable approach. This article describes how automated laboratory platforms, Process Analytical Technology (PAT), structured data management, and modelling tools are used at Siegfried to improve development efficiency and process robustness to support more reliable transfer to manufacturing. Selected case studies illustrate the application of inline and in situ monitoring to reaction and crystallization development, while modelling supports rational scale-up of mixing, distillation, filtration, and centrifugation operations. Continuous flow chemistry is also discussed to widen the accessible process window while improving safety, control, and industrial relevance.