(725a) Leveraging COSMO-RS for Chemical Development and Scale-up in the Pharmaceutical Industry

Chemical development and scale-up in the pharmaceutical industry are critical stages in the journey from drug discovery to commercialization. The efficient and robust transition from laboratory-scale synthesis to large-scale manufacturing is paramount for ensuring product quality, safety, sustainability, and cost-effectiveness. However, this process is often hindered by challenges such as limited experimental data, complex reaction pathways, and stringent regulatory requirements.[1] Indeed traditional approaches rely heavily on empirical experimentation, which is time-consuming, resource-intensive, and often limited by the availability of experimental data. Furthermore, the complexity of modern drug molecules and the stringent regulatory landscape necessitate innovative strategies for process optimization and formulation design.

In recent years, computational methods have emerged as indispensable tools for addressing these challenges and accelerating the development timeline.[2] Among these methods, COSMO-RS (Conductor-like Screening Model for Real Solvents) stands out for its ability to predict thermodynamic properties and phase behavior of complex chemical systems.[3] Rooted in quantum chemistry and statistical thermodynamics principles, COSMO-RS, offers a promising contribute for efficient chemical process development and scale-up. Unlike traditional empirical methods, it provides a molecular-level understanding of solvent-solute interactions, leveraging molecular descriptors and advanced algorithms to simulate complex chemical systems, offering insights into the underlying physicochemical phenomena governing solvation and phase behavior. [4-6]

The present work demonstrates COSMO-RS’ capacity to develop robust distillations, liquid-liquid extractions, and crystallization processes through its accurate predictions of vapor-liquid equilibria (VLE), liquid-liquid equilibria (LLE) and solid-liquid equilibria (SLE), prediction of partition coefficients and distribution ratios for target solutes and estimation of solubility data.

Overall, a successful assessment of Cosmo-RS for simulating these unit operations was accomplished, combining theoretical data, experimental validation, and practical applications with very positive impact on operational safety, cycle time and resource management.

References

[1] Federsel, H. Chemical Process Research and Development in the 21st Century: Challenges, Strategies, and Solutions from a Pharmaceutical Industry Perspective. Acc. Chem. Res. 2009, 42, 5, 671–680

[2] Rogers, A.; Ierapetritou, M. Challenges and opportunities in modeling pharmaceutical manufacturing processes. Comput. Chem. Eng. 2015, 81, 32-39

[3] Klamt, A. The COSMO and COSMO-RS solvation models. Wiley Interdiscip. Rev. Comput. Mol. Sci. 2017

[4] Klamt, A. Prediction of the mutual solubilities of hydrocarbons and water with COSMO-RS. Fluid Phase Equilibria, 206 (1), 2003, 223-235

[5] Klamt, A. COSMO-RS for aqueous solvation and interfaces, Fluid Phase Equilibria, 2016, 407, 152-158

[6] Freire, M.; Santos, L.M.N.B.F.; Marrucho, I.M.; Coutinho, J.A.P. Evaluation of COSMO-RS for the prediction of LLE and VLE of alcohols + ionic liquids. Fluid Phase Equilibria, 2007, 255 (2), 167-178

[7] Putnam, R.; Taylor, R.; Klamt, A.; Eckert, F.; Schiller, M. Prediction of Infinite Dilution Activity Coefficients Using COSMO-RS. Ind. Eng. Chem. Res. 2003, 42, 3635-3641