The main achievement of this work has been the development of a methodology that takes advantage of existing thermodynamic and process insights to provide feasible and near optimum solutions for the selection of solvents and anti-solvents for the synthesis and operational design of crystallisation processes. A robust and reliable, generic model-based crystallisation computational framework specifically targeting the pharmaceutical industry was developed that can predict and optimize the production of crystalline API materials, with the desired yield and purity based on solvent selection and selection of mode of crystallisation.
The computational framework explores the synergistic combination of multi-component multiphase flash calculations, phase equilibria phenomena, and process systems engineering methods, to establish the presence of solid-liquid equilibria of the components in a given feed, and the identification of the sequence of the precipitating solids under varying temperature and concentration changes. These computational capabilities allow the developed framework to provide the insight to exploit the change in the solubility boundaries and regions with temperature variation and concentration changes and to be used as a screening mechanism to quickly determine the most appropriate solvent(s) and type of crystallisation process/processes for a given application. It has been developed for faster process design and process understanding, that can be used in industry as a decision making tool during the conceptual design phase, and as a design or optimisation tool for retrofitting an existing process to maximize the overall process performance.
The successful embedding of the developed crystallisation computational framework within the commercial process simulation software CHEMCAD improves its robustness and extend its computational capabilities. The computations within the Solvent Selection module has access to a full range of thermodynamics models and correlations, a comprehensive database of compounds and their pure and mixture properties, and rigorous computational algorithms for process calculations and equipment design of the commercial simulator. In addition, the software vendors regularly deliver updates for their programs to fix bugs and to deliver new functionality including the updating and inclusion of new property and thermodynamic models and methods that enhance the accuracy of the predictive methods. Through several graphical user interfacing platforms, the user is able perform numerous calculations to comprehensively evaluate the process, economic and environmental impact of solvent selection.
The computational framework creates opportunities, not only for finding near optimal operating strategies, but also to investigate and develop a comprehensive understanding of the process, economic
160 | P a g e and environmental impact of solvent and anti-solvent selection in crystallisation process. Specifically, the developed framework consists of several algorithms and subroutines that enables the following spectrum of computational capabilities:
• The optimum operability conditions for the crystallizer can be identified with minimal thermodynamic information on the system, by using multiphase flash calculations. Starting with just the chemical structure, and using the predictive thermodynamics property models like UNIFAC and other group contribution methods, the Solid-Liquid-Vapour equilibria (SLVE) phase behaviour can be calculated. The conditions at which there is a phase change from liquid to solid of a component of interest represents the onset of the crystallisation process for that component. By determining that change in the amount of solid formation by flash calculations due to temperature or composition change or both, the extend of crystal formation can be determined.
• The various eutectic temperatures and compositions that exist in the system can be predicted, and data can be generated for developing various types of phase diagrams and solubility curves.
These allow for the overall composition space to be visualised and the separation barriers to be examined. In particular, the analysis of systems with multi-components and multiple saturation points is enabled.
• The operations such as heating, cooling, solvent addition, and solvent removal, can be simulated to systematically evaluate process alternatives. This enables the user to filter and screen solvents, and evaluate the effects of co-solvents, anti-solvents, other components, and impurities on the solute’s solubility, in a specified temperature and composition range.
• The identification of the operating conditions that give maximum recovery of a desired compound, with a certain solvent or solvent mixture, and the calculation of the percent recoveries, and the total energy requirements (heating/cooling), under various operating conditions is enabled. The tool can be used to establish operating strategies, which may involve a combination of “cooling/heating”, “co-solvent/anti-solvent addition”, and “Evaporation”
steps to meet the process objectives. All the important process alternatives can also be identified by this procedure, and can be systematically evaluated for quick screening purposes. The results obtained from this procedure will be mainly helpful in obtaining a quick, preliminary estimate of the best alternative.
• The framework can also be used to perform sensitivity analyses on the various input parameters to the process, and therefore identify important design variables in the process that will have the greatest impact on the overall performance.
• The inclusion of financial and environmental impact algorithms enhances and extend the applicability for significant and realistic comparative studies. The comparative investigation of the process engineering implications of the various solvents and modes of crystallisation can
161 | P a g e be undertaken. Once the desired production rate is established, the effect each solvent will have on the size of various key equipment required, can be determined, along with the associated capital expenditure. In addition, the operational expenses and environmental impact associated with a selected solvent / anti-solvent and selected mode of crystallisation can be evaluated.
A series of validation processes and applications have shown that the thermodynamic and process insights embedded in this computation framework can be exploited to provide solutions for the synthesis and operational design of crystallisation processes, and in particular the impact a selected solvent, anti- solvent and mode of crystallisation may have on the overall performance of the process, as the goal of this thesis was originally set to be.
A key limitation of this methodology is that the accuracy of the predictions for complex molecules is dependent on the accuracy of predictive pure and mixture property models and predictive phase equilibria models that exist within the commercial simulator. Since the simulator allows for the inclusion of experimentally measured properties and user defined property models, this may for a specific purpose improve the accuracy for a particular application.
In summary, the innovative computational framework developed in this work and embedded into a commercial process simulator, provides a simple and fast way of conducting comparative studies to provide feasible, near optimum solutions that could be used for screening design and operational alternatives, and eventually be used for further rigorous optimisation studies. It presents a robust conceptual design tool for the rapid screening solvents and operational modes for crystallisation.
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