Dry powder inhalers (DPIs), used as a means for pulmonary drug delivery, typically contain a combination of active pharmaceutical ingredient (API) and significantly larger carrier particles. The micro-sized drug particles — which have a strong propensity to aggregate and poor aerosolization performance — mixed with significantly large carrier particles that are unable to penetrate the mouth-throat region to deagglomerate and entrain the smaller API particles in the inhaled airflow. The performance of a DPI, therefore, depends on entrainment the carrier-API combination particles and the time and thoroughness of the deagglomeration of the individual API particles from the carrier particles. Since DPI particle transport is significantly affected by particle-particle interactions, very different particles sizes and shapes, various forces including electrostatic and van der Waals forces, they present significant challenges to Computational Fluid Dynamics (CFD) modelers to model regional lung deposition from a DPI. In the current work, we present a novel high fidelity CFD discrete element modeling (CFD-DEM) and sensitivity analysis framework for predicting the transport of DPI carrier and API particles. The work integrates exascale capable CFD-DEM and sensitivity analysis capabilities by leveraging the Department of Energy (DOE) laboratories libraries: Multiphase Flow Interface Flow Exchange (MFiX) for CFD-DEM, and Trilinos for leading-edge portable/scalable linear algebra. We carried out a sensitivity analysis of various formulation properties and their effects on particle size distribution with Dakota, an open source software designed to exploit High-Performance Computing (HPC) capabilities of a massively parallel supercomputer. We developed wrappers to exchange information among these state-of-the-art tools for DPI.