Using AI/ML to predict blending performance and process sensitivity for Continuous Direct Compression (CDC)

Author:

Jones-Salkey O.ORCID,Windows-Yule C.R.K.,Ingram A.,Stahler L.ORCID,Nicusan A.L.ORCID,Clifford S.ORCID,Martin de Juan L.,Reynolds G.K.ORCID

Funder

Engineering and Physical Sciences Research Council

AstraZeneca

Publisher

Elsevier BV

Reference38 articles.

1. Granular mixing and segregation in a horizontal rotating drum: a simulation study on the impact of rotational speed and fill level;Arntz;AIChE J.,2008

2. Impact of blend properties and process variables on the blending performance;Bekaert;Int. J. Pharm.,2022

3. Continuous direct compression: Development of an empirical predictive model and challenges regarding PAT implementation;Bekaert;Int. J. Pharm. X,2022

4. In-depth analysis of the long-term processability of materials during continuous feeding;Bekaert;Int. J. Pharm.,2022

5. Julia: A fresh approach to numerical computing;Bezanson;SIAM Rev.,2017

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