Ice-nucleating particles (INPs) in soils are complex mixtures of mineral dust and biological material, yet the influence of particle mixing state on ice nucleation activity remains poorly constrained. Here, we generated synthetic soils using montmorillonite and Snomax to evaluate the suitability of current analytical methods for characterizing and predicting the ice nucleation activity of complex particle mixtures. Particle composition was characterized using single particle mass spectrometry (SPMS) and computer controlled scanning electron microscopy with electron dispersive x-ray (CCSEM/EDX), as well as Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS) for surface chemical analysis. Ice nucleation experiments were conducted using a Continuous Flow Diffusion Chamber (CFDC). CCSEM/EDX classified particles predominantly as externally mixed while SPMS demonstrated greater sensitivity to Snomax and identified more internally-mixed particles. Residual particles from both techniques showed enhanced biological markers compared to the bulk population. Frozen fractions did not scale with mass mixing ratios, and simulations indicated that mixing state had minimal effect on ice nucleation activity when total Snomax mass was conserved. We also found some limited evidence that incorporating particle mixing state from measurements improves simulated frozen fractions. These results demonstrate that accurate prediction of INP activity in dust-biological mixtures requires constraints on the abundance and particle-level distribution of active biological material, rather than bulk or population-average compositional descriptions alone.