posted on 2016-07-15, 08:53authored byKeddon Powell, Ali N. Saleemi, Chris Rielly, Zoltan Nagy
In this study, an automated intelligent decision support (IDS) framework was applied to monitor the continuous crystallization of form I paracetamol (PCM) and determine steady-state operation. A modified single-stage mixed suspension mixed product removal (MSMPR) crystallizer was used to investigate methods to minimize early onset of fouling and encrustation by carrying out crystallizations in the presence and absence of hydroxyl propyl methyl cellulose (HPMC) additive. The effectiveness of HPMC toward controlling the crystallization process and alleviating fouling and encrustation for prolonged operation of the MSMPR was investigated over a range of concentrations. HPMC was found to suppress nucleation and growth, thereby controlling the crystallization and alleviating fouling and encrustation over extended operating periods. HPMC also affected the product crystal morphology, leading to predominantly tabular shaped crystals. Steady state in the MSMPR was characterized using the IDS, which consisted of an integrated and ancillary array of process analytical technologies (PAT), including the application of Raman spectroscopy with multivariate calibration for solution phase concentration measurement.
Funding
The authors would like to thank the EPSRC (EP/I033459/1)
and the Centre for Continuous Innovation in Continuous
Manufacturing and Crystallization (CMAC) for the financial
support of this work and the European Research Council under
the European Union’s Seventh Framework Program (FP7/
2007-2013)/ERC grant agreement no. [280106-CrySys] (for
equipment and financial support). Special thanks to Rajesh
Gurang for creating the TOC artwork.
History
School
Aeronautical, Automotive, Chemical and Materials Engineering
Department
Chemical Engineering
Published in
ORGANIC PROCESS RESEARCH & DEVELOPMENT
Volume
20
Issue
3
Pages
626 - 636 (11)
Citation
POWELL, K.A. ... et al., 2016. Monitoring continuous crystallization of paracetamol in the presence of an additive using an integrated PAT array and multivariate methods. Organic Process Research and Development, 20 (3), pp. 626 - 636.
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