Dynamic flow experiments for data-rich optimization

被引:2
|
作者
Williams, Jason D. [1 ]
Sagmeister, Peter [1 ]
Kappe, C. Oliver [1 ,2 ]
机构
[1] Ctr Continuous Flow Synth & Proc CC FLOW, Res Ctr Pharmaceut Engn GmbH RCPE, Inffeldgasse 13, A-8010 Graz, Austria
[2] Graz Univ, NAWI Graz, Inst Chem, Heinrichstr 28, A-8010 Graz, Austria
关键词
Flow chemistry; Data-rich experimentation; Process analytical technology; Dynamic flow experiments; GENERATION; KINETICS; MERITS; GREEN;
D O I
10.1016/j.cogsc.2024.100921
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
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.
引用
收藏
页数:8
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