Model-based solvent selection for the synthesis and crystallisation of pharmaceutical compounds
File(s)
Published version
OA Location
Author(s)
Muhieddine, Mohamad H
Viswanath, Shekhar K
Armstrong, Alan
Galindo, Amparo
Adjiman, Claire S
Type
Journal Article
Abstract
The pharmaceutical industry needs design tools to identify greener and more resource-efficient process routes. Current model-based solvent selection methodologies often focus on the choice of solvent in a single unit operation, with fixed operating conditions. In particular, the two key stages of synthesis and separation are usually treated independently. This often results in the use of different solvents for each processing task, which typically requires energy-intensive solvent swap operations. In the current paper, we present a novel computer-aided approach based on computer-aided mixture/blend design (CAMbD) that couples property prediction with simple process models and optimisation to simultaneously identify optimal solvents and anti-solvents, compositions and process conditions for integrated synthesis and crystallisation. Solvents are chosen using key performance indicators (KPIs) that quantify mass efficiency and product quality. The proposed methodology is illustrated by identifying promising reaction and crystallisation solvents for the synthesis of mefenamic acid from 2,3-dimethylaniline and 2-chlorobenzoic acid. Furthermore, multi-objective optimisation is deployed to highlight the trade-offs between the solvent or process E-factor and safety indicators, and between the solvent E-factor and crystal yield. The inclusion of mass-based KPIs and safety specifications ensures that only high-performance solvents are chosen. The findings of our approach are expected to guide the rational selection of solvents for greener pharmaceutical manufacturing during early-stage process development.
Date Issued
2022-12-31
Date Acceptance
2022-09-15
Citation
Chemical Engineering Science (CES), 2022, 264
ISSN
0009-2509
Publisher
Elsevier
Journal / Book Title
Chemical Engineering Science (CES)
Volume
264
Copyright Statement
© 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
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Subjects
AIDED MOLECULAR DESIGN
BLENDS
CAMbD
Crystal yield
Engineering
Engineering, Chemical
FRAMEWORK
Green chemistry
GREEN CHEMISTRY
IBUPROFEN
Mefenamic acid
METHODOLOGY
MIXTURE DESIGN
PERSPECTIVE
Process E-factor
Science & Technology
Solvent E-factor
TECHNOECONOMIC EVALUATION
Technology
WIDE DYNAMIC-MODEL
Publication Status
Published
Article Number
118125
Date Publish Online
2022-09-22