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利用动态流动实验同时建立反应模型和分析模型以加速工艺开发。

Simultaneous reaction- and analytical model building using dynamic flow experiments to accelerate process development.

作者信息

Sagmeister Peter, Melnizky Lukas, Williams Jason D, Kappe C Oliver

机构信息

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

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

出版信息

Chem Sci. 2024 Jul 1;15(31):12523-12533. doi: 10.1039/d4sc01703j. eCollection 2024 Aug 7.

DOI:10.1039/d4sc01703j
PMID:39118626
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11304546/
Abstract

In modern pharmaceutical research, the demand for expeditious development of synthetic routes to active pharmaceutical ingredients (APIs) has led to a paradigm shift towards data-rich process development. Conventional methodologies encompass prolonged timelines for the development of both a reaction model and analytical models. The development of both methods are often separated into different departments and can require an iterative optimization process. Addressing this issue, we introduce an innovative dual modeling approach, combining the development of a Process Analytical Technology (PAT) strategy with reaction optimization. This integrated approach is exemplified in diverse amidation reactions and the synthesis of the API benznidazole. The platform, characterized by a high degree of automation and minimal operator involvement, achieves PAT calibration through a "standard addition" approach. Dynamic experiments are executed to screen a broad process space and gather data for fitting kinetic parameters. Employing an open-source software program facilitates rapid kinetic parameter fitting and additional optimization within minutes. This highly automated workflow not only expedites the understanding and optimization of chemical processes, but also holds significant promise for time and resource savings within the pharmaceutical industry.

摘要

在现代药物研究中,对快速开发活性药物成分(API)合成路线的需求已导致向数据丰富的工艺开发范式转变。传统方法在反应模型和分析模型的开发上都需要较长时间。这两种方法的开发通常分属不同部门,且可能需要反复优化过程。为解决这一问题,我们引入了一种创新的双重建模方法,将过程分析技术(PAT)策略的开发与反应优化相结合。这种集成方法在多种酰胺化反应和API苄硝唑的合成中得到了体现。该平台具有高度自动化和最少操作人员参与的特点,通过“标准加入”方法实现PAT校准。进行动态实验以筛选广泛的工艺空间并收集用于拟合动力学参数的数据。使用开源软件程序可在几分钟内快速进行动力学参数拟合和进一步优化。这种高度自动化的工作流程不仅加快了对化学过程的理解和优化,也为制药行业节省时间和资源带来了巨大希望。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b7b3/11304546/fd1e06b36339/d4sc01703j-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b7b3/11304546/568a7b2f7a88/d4sc01703j-f1.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b7b3/11304546/00313e490f84/d4sc01703j-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b7b3/11304546/b9639fc46c82/d4sc01703j-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b7b3/11304546/14ce5546fb49/d4sc01703j-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b7b3/11304546/fd1e06b36339/d4sc01703j-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b7b3/11304546/568a7b2f7a88/d4sc01703j-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b7b3/11304546/5fa1b9ba684a/d4sc01703j-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b7b3/11304546/00313e490f84/d4sc01703j-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b7b3/11304546/b9639fc46c82/d4sc01703j-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b7b3/11304546/14ce5546fb49/d4sc01703j-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b7b3/11304546/fd1e06b36339/d4sc01703j-f6.jpg

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