Automated In Silico Energy Mapping of Facet-Specific Interparticle Interactions

Particle-particle interactions impact the process-ability and performance of drug products. Faceted particulates exhibit distinct surface chemistries that affect their adhesion, causing downstream processing challenges such as poor flow, punch sticking, and compaction. Currently, there is a lack of tools to assist formulators in predicting these challenges based on particle properties. Here, we present a methodology for navigating the energy landscape of interparticle interactions. We used molecular mechanics to calculate the interactions between slabs of molecules representing distinct facets. The workflow enables a rapid assessment of the total energy landscape between interacting particles, providing insight into the effects of different surface chemistries and molecular topologies. Previously, the strongest interaction (lowest energy) was used to calculate the propensity to adhere, but we demonstrate that this does not always predict an accurate description of the likely surface interactions. We chose paracetamol to demonstrate the application of this methodology. The most cohesive facets were (101) and (10-1). Comparing surface interactions between particles allows a ranking of the most energetically compatible surfaces. The significance of this ranking and understanding how surface chemistry can impact interparticle interactions is a step toward assisting formulation decisions and improvements in product performance.