Abstract

Choosing a solvent and an antisolvent for a new crystallization process is challenging due to the sheer number of possible solvent mixtures and the impact of solvent composition and crystallization temperature on process performance. To facilitate this choice, we present a general computer aided mixture/blend design (CAMbD) formulation for the design of optimal solvent mixtures for the crystallization of pharmaceutical products. The proposed methodology enables the simultaneous identification of the optimal process temperature, solvent, antisolvent, and composition of solvent mixture. The SAFT-γ Mie group-contribution approach is used in the design of crystallization solvents; based on an equilibrium model, both the crystal yield and solvent consumption are considered. The design formulation is implemented in gPROMS and applied to the crystallization of lovastatin and ibuprofen, where a hybrid approach combining cooling and antisolvent crystallization is compared to each method alone. For lovastatin, the use of a hybrid approach leads to an increase in crystal yield compared to antisolvent crystallization or cooling crystallization. Furthermore, it is seen that using less volatile but powerful crystallization solvents at lower temperatures can lead to better performance. When considering ibuprofen, the hybrid and antisolvent crystallization techniques provide a similar performance, but the use of solvent mixtures throughout the crystallization is critical in maximizing crystal yields and minimizing solvent consumption. We show that our more general approach to rational design of solvent blends brings significant benefits for the design of crystallization processes in pharmaceutical and chemical manufacturing.

Highlights

  • The choice of solvent, or solvents, can drastically affect the outcome and efficiency of the crystallization process. This impact is seen in changes to the solubility of the active pharmaceutical ingredient (API), which affects both the potential crystal yield of the API and the total volume of solvent required to perform a crystallization

  • The formulation is implemented in gPROMS version 6.0.2, applying gSAFT to perform calculations using the statistical associating fluid theory (SAFT)-γ Mie group-contribution thermodynamic platform

  • A general formulation has been presented based on a computer aided mixture/blend design (CAMbD) framework, with an aim to guide experiments toward the identification of optimal solvent blends for the crystallization of pharmaceutical compounds, reducing the time and costs typically associated with solvent selection

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Summary

Introduction

More than 80% of small-molecule pharmaceuticals are delivered in a solid form,[1] such as tablets and aerosols; because of this, pharmaceutical production is dependent on effective crystallization systems. The choice of solvent, or solvents, can drastically affect the outcome and efficiency of the crystallization process. This impact is seen in changes to the solubility of the active pharmaceutical ingredient (API), which affects both the potential crystal yield of the API and the total volume of solvent required to perform a crystallization. These effects can be observed by changing the compound used as a solvent or when solvent mixtures are employed. Exploiting the enhanced performance of mixtures, raises many challenges for solvent selection

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