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Moisture-induced flow variabilities in pharmaceutical blends lead to multiple impediments during manufacturing of solid dosage formulations. Processing and storage humidity conditions both govern the moisture contents of the pharmaceutical mixtures and bear significant impact on the final product quality. In this study, experimentally validated discrete element method-based computational models along with statistical formalism have been implemented to develop a predictive tool for moisture-induced cohesion in binary and tertiary mixtures. V-blending was applied to prepare the pharmaceutical blends, and mixing characterization was performed using a Raman PhAT probe. Optimum fill volume was established for the mixing conditions to minimize static charging due to blender wall interactions on the pharmaceutical powders. A simplex-centroid (augmented) design for 3-component system was implemented to predict and quantify the nonlinear behavior of moisture-induced cohesion between the pharmaceutical powders based on their systematic hopper discharge studies (experiments and simulations). A methodical implementation of these quantification tools was hence performed to validate a design space that enables an approach to the appropriate selection of blend concentrations that achieve minimum mixture flow variability across different humidity conditions.