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连续流中多步合成的高级实时过程分析*。

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

机构信息

Center for Continuous Flow Synthesis and Processing (CCFLOW), Research Center Pharmaceutical Engineering GmbH (RCPE), Inffeldgasse 13, 8010, Graz, Austria.

Institute of Chemistry, University of Graz, NAWI Graz, Heinrichstrasse 28, 8010, Graz, Austria.

出版信息

Angew Chem Int Ed Engl. 2021 Apr 6;60(15):8139-8148. doi: 10.1002/anie.202016007. Epub 2021 Feb 24.

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.

摘要

在多步连续流动化学中,实时研究复杂的反应混合物是一项重大挑战,但也提供了增强反应理解和控制的机会。我们报告了将四种互补的过程分析技术工具(NMR、UV/Vis、IR 和 UHPLC)集成到活性药物成分美沙拉嗪的多步合成中的情况。该合成路线利用流动处理进行硝化、高温水解和氢化反应,以及三个在线分离。开发了先进的数据分析模型(间接硬建模、深度学习和偏最小二乘回归),以实时、在合成途径的多个点定量所需的产物、中间体和杂质。该系统的功能已通过稳态和动态实验得到证明,代表了数据驱动的连续流动合成的重要一步。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3ed/8048486/5a6eb5f17faf/ANIE-60-8139-g005.jpg

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