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Advanced Real-Time Process Analytics for Multistep Synthesis in Continuous Flow
preprintrevised on 03.12.2020, 08:11 and posted on 03.12.2020, 12:12 by Peter Sagmeister, René Lebl, Ismael Castillo, Jakob Rehrl, Martin Horn, Julia Kruisz, Martin Sipek, Stephan Sacher, David Cantillo, Jason Williams, C. Oliver Kappe
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 orthogonal Process Analytical Technology tools (NMR, UV/vis, IR and UHPLC) in the multistep synthesis of an Active Pharmaceutical Ingredient, mesalazine. This synthetic route makes optimal use of flow processing for nitration, high temperature hydrolysis and hydrogenation steps, as well as three inline separations. Advanced data analysis models were developed (indirect hard modelling, 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.