Time-of-flight secondary ion mass spectrometry (ToF-SIMS) instruments can rapidly produce large complex data sets. Within each spectrum, there can be hundreds of peaks. A typical 256×256 pixel image contains 65,536 spectra. If this is extended to a 3D image, the number of spectra in a given data set can reach the millions. The challenge becomes how to process these large data sets while taking into account the changes and differences between all the peaks in the spectra. This is particularly challenging for biological materials that all contain the same types of proteins and lipids, just in varying concentrations and spatial distributions. This data analysis challenge is further complicated by the limitations in the ion yield of higher mass, more chemically specific species, and potentially by the processing power of typical computers. Herein we briefly discuss analysis methodologies including univariate analysis, multivariate analysis (MVA) methods, and some of the limitations of ToF-SIMS analysis of biological materials.