Drug-polymer compatibility prediction via COSMO-RS

Area of Science:

• Computational chemistry
• Materials science
• Pharmaceutical sciences

Background:

• Solid-liquid equilibrium (SLE) is crucial for understanding active pharmaceutical ingredient (API) and polymer interactions in drug formulation.
• Predictive modeling can accelerate the screening of API-polymer compatibility, reducing experimental workload.

Purpose of the Study:

• To predict the SLE curves of ten APIs with polyvinylpyrrolidone (PVP) K12 using the Conductor-like Screening Model for Real Solvents (COSMO-RS).
• To compare the performance of two COSMO-RS prediction strategies: a traditional and an expedited approach.
• To validate the predicted SLE curves against experimental data obtained via the step-wise dissolution (S-WD) method.

Main Methods:

• Utilized the Conductor-like Screening Model for Real Solvents (COSMO-RS) for theoretical SLE curve prediction.
• Employed two distinct COSMO-RS methodologies: a traditional and an expedited approach.
• Experimentally determined SLE data using the step-wise dissolution (S-WD) technique for validation.

Main Results:

• COSMO-RS predictions showed satisfactory agreement with experimental SLE data for most API-PVP K12 systems.
• The traditional COSMO-RS approach yielded more reliable predictions compared to the expedited approach.
• Only two predictions, both from the expedited approach, exhibited significant disagreement with experimental results.

Conclusions:

• The traditional COSMO-RS approach is recommended for predicting API-polymer SLE curves.
• COSMO-RS serves as an effective computational tool for rapid screening of API-polymer compatibility, especially for novel APIs with limited data.
• This predictive capability can significantly streamline early-stage drug development and formulation design.