Advanced Real‐Time Process Analytics for Multistep Synthesis in Continuous Flow**

TLDR

Real‑time analysis of complex mixtures in multistep continuous flow chemistry is challenging but can improve reaction understanding and control. The study integrates NMR, UV/Vis, IR, and UHPLC into the multistep synthesis of mesalazine. The synthesis uses flow nitration, high‑temperature hydrolysis, hydrogenation, and three inline separations, while advanced models—indirect hard modeling, deep learning, and PLS regression—quantify products, intermediates, and impurities in real time. Steady‑state and dynamic experiments demonstrate the system’s capabilities, marking a significant advance in data‑driven continuous flow synthesis.

Abstract

In multistep continuous flow chemistry, studying complex reaction mixtures in real time is a significant challenge, but provides an opportunity to enhance reaction understanding and control. We report the integration of four complementary process analytical technology tools (NMR, UV/Vis, IR and UHPLC) in the multistep synthesis of an active pharmaceutical ingredient, mesalazine. This synthetic route exploits flow processing for nitration, high temperature hydrolysis and hydrogenation reactions, as well as three inline separations. Advanced data analysis models were developed (indirect hard modeling, deep learning and partial least squares regression), to quantify the desired products, intermediates and impurities in real time, at multiple points along the synthetic pathway. The capabilities of the system have been demonstrated by operating both steady state and dynamic experiments and represents a significant step forward in data-driven continuous flow synthesis.