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.