数据丰富的动态优化流动实验

IF 9.3 2区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY
Jason D. Williams , Peter Sagmeister , C. Oliver Kappe
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引用次数: 0

摘要

流动化学对化学工业生产的影响越来越大,但在这些连续工艺的开发过程中仍存在重大障碍。动态流动实验有可能以数据丰富的方式实现工艺开发的民主化和加速,从而减少时间和材料浪费。基于所收集数据的模型也可用于减少生产环境中的浪费。在此,我们总结了有关动态流程实验的文献报告(其中大部分是过去 5 年的报告),重点介绍了实验设计、流程分析和所得数据的利用。最后,我们详细讨论了制药开发中的动态实验实例。未来几年,动态实验在工业环境中的普及无疑将促进更环保的生产流程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dynamic flow experiments for data-rich optimization

Flow chemistry is having an increasing influence on manufacturing in the chemical industry, but significant barriers remain in the development of these continuous processes. Dynamic flow experiments have the potential to democratize and accelerate process development in a data-rich manner, reducing time and material wastage. Models based on the data gathered can also be leveraged to decrease waste in a manufacturing environment. Here, we summarize the literature reports of dynamic flow experiments (most of which are from the past 5 years), with a focus on experiment design, process analytics, and utilization of the resulting data. Finally, an example of dynamic experiments in pharmaceutical development is discussed in detail. A higher uptake of dynamic experiments in industrial environments in the coming years will undoubtedly facilitate greener manufacturing processes.

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来源期刊
CiteScore
16.00
自引率
2.20%
发文量
140
审稿时长
103 days
期刊介绍: The Current Opinion journals address the challenge specialists face in keeping up with the expanding information in their fields. In Current Opinion in Green and Sustainable Chemistry, experts present views on recent advances in a clear and readable form. The journal also provides evaluations of the most noteworthy papers, annotated by experts, from the extensive pool of original publications in Green and Sustainable Chemistry.
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