Skip to main content
Prepare for an exciting September! Each week, we'll examine the latest trends in PAT, offering fresh insights straight from recent conferences. Your perspective matters, so we encourage you to share your thoughts as well. Stay informed, stay engaged, and let's explore these cutting-edge developments together. https://bit.ly/3Xw0X7k
3.137.212.137

Modeling and simulation studies of a novel coupled plug flow crystallizer for the continuous separation of conglomerate-forming enantiomers

By Majumder, Aniruddha

Published on CMKC

Abstract

Separation of enantiomers is a major concern in pharmaceutical industries due to the different therapeutic activities exhibited by the enantiomers. Preferential crystallization is an attractive means to separate the conglomerate-forming enantiomers. In this work, a simulation study is presented for a proposed novel preferential crystallization configuration that involves coupled plug flow crystallizers (PFCs). The PFCs are coupled through liquid phase exchange which helps the enrichment of the preferred enantiomer in the liquid phase. A set of coupled population balance equations (PBEs) are used to describe the evolution of the crystal size distribution (CSD) in the PFCs. The PBEs and the relevant mass balance equations are solved using the high-resolution finite-volume method. The simulation results predict that the proposed configuration has higher productivity compared to the currently used crystallization configurations while maintaining the same level of purity. Moreover, the effect of process variables, such as the extent of liquid phase exchange and the location of the PFC where liquid phase exchange occurs, are studied. The insights obtained from this simulation study will be useful in design, development, and optimization of such novel crystallization platforms.

Journal

Processes. Volume 6, 12, 2018, 247

DOI

10.3390/pr6120247

Type of publication

Peer-reviewed journal

Affiliations

  • University of Aberdeen

Article Classification

Research Article

Classification Areas

  • Modelling

Tags