(165e) Prediction of Liquid-Liquid Partitioning and Solubility of APIs with the SAFT-γ Mie Approach

Authors: 
Hutacharoen, P., Imperial College London
Dufal, S., Imperial College
Papaioannou, V., Imperial College London
Adjiman, C. S., Imperial College London
Jackson, G., Imperial College London
Galindo, A., Imperial College London
Lipophilicity is a fundamental physicochemical property in drug discovery and is usually quantified from the partitioning equilibrium of solute molecules between water and an immiscible organic solvent. The most popular system in this context is the 1-octanol + water mixture. The partitioning of solutes in aqueous alkane systems (e.g., hexane + water and hexadecane + water) is also of interest for drug discovery and the difference between the partition coefficients serves as a measure of the hydrogen bonding potential of a molecule. The solubility of APIs in both aqueous and organic solvents is an essential property for drug development and manufacturing. It serves as essential information in the design of the downstream processes of APIs.

A general approach to predict the solubility and partition coefficients in octanol+water (KOW) and alkane+water (Kalk) systems is developed. The core of our predictive framework lies in the use of the recently developed group-contribution SAFT-γ Mie approach [1-4]. SAFT-γ Mie is a predictive equation of state which allows one to determine the thermo-physical properties of molecules in terms of the constituent functional groups that represent their unique molecular identity. These functional groups are then modelled as fused spherical segments that interact via Mie (generalized Lennard-Jones) potentials of variable repulsive and attractive ranges. The parameters for each functional group are developed from fluid-phase equilibrium data for simple compounds and, once estimated, they are applied to the study of more complex multifunctional molecules in a predictive manner. This key feature of the SAFT-γ Mie approach enables the prediction of the properties of organic molecules in various solvents and solvent mixtures over wide thermodynamic conditions without the need for experimental solubility data for a specific molecule.

The necessary alkane-water and octanol-water group interactions are established providing an excellent description of the partition coefficients of several families of organic compounds which are used to test the reliability of the models. The SAFT-γ Mie models are then applied to predict the KOW and solubility of various APIs in different organic solvents; the results are found to be in excellent agreement with the experimental data. The APIs employed in this study range from a relatively simple molecule, azelaic acid, to multifunctional molecules, such as ibuprofen, ketoprofen, lovastatin, and simvastatin. No experimental data related to the API are used in the KOW prediction. For the solubility calculation, in addition to the molecular structure, a few properties of the pure API are required, namely the melting temperature, heat of fusion, and the heat capacity difference between the liquid and the solid state of API. This work highlights the extension of the SAFT-γ Mie equation of state in predicting important thermodynamic properties of complex multifunctional molecules in different solvents and demonstrates that the appraoch can be employed as a novel predictive platform for the prediction of important API properties from molecular structure alone.

References

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Acknowledgements

We gratefully acknowledge financial support from Pfizer Inc.