流动化学
过程分析技术
化学
连续流动
计算机科学
工艺工程
过程(计算)
分析
活性成分
组合化学
生物系统
生化工程
在制品
数据挖掘
工程类
生物信息学
生物
操作系统
运营管理
作者
Peter Sagmeister,René Lebl,Ismaël Castillo,Jakob Rehrl,Julia Kruisz,Martin Sipek,Martin Horn,Stephan Sacher,David Cantillo,Jason D. Williams,C. Oliver Kappe
标识
DOI:10.1002/anie.202016007
摘要
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.
科研通智能强力驱动
Strongly Powered by AbleSci AI