Design of Experiments (DoE) and Process Optimization. A Review of Recent Publications

Statistical design of experiments (DoE) is a powerful tool for optimizing processes, and it has been used in many stages of API development. This review summarizes selected publications from Organic Process Research & Development using DoE to show how processes can be optimized efficiently and how DoE findings may be applied to scale-up.

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PID https://www.doi.org/10.1021/op500169m.s001
URL http://dx.doi.org/10.1021/op500169m.s001
URL https://figshare.com/articles/Design_of_Experiments_DoE_and_Process_Optimization_A_Review_of_Recent_Publications/2107105
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Access Right Open Access
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Author Weissman, Steven A.
Author Anderson, Neal G.
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Collected From figshare
Hosted By figshare
Publication Date 2016-01-01
Publisher Figshare
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Language UNKNOWN
Resource Type Dataset
system:type dataset
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Source https://science-innovation-policy.openaire.eu/search/dataset?datasetId=r37980778c78::2fdbe02e3a7ca4ee26531e169257e264
Author jsonws_user
Last Updated 29 December 2020, 03:58 (CET)
Created 29 December 2020, 03:58 (CET)