Time-of-flight secondary ion mass spectrometry (TOF-SIMS) data are complex, even for the simplest systems. Yet it is within this complexity that information about sample composition, molecular orientation, surface order, chemical bonding, sample purity, etc., is contained. The challenge is how to easily extract this information from the spectra and images. Multivariate analysis (MVA) has shown promise in taming the complexity challenges presented by TOF-SIMS data while using all the information in the entire spectrum. The recent success of MVA methods such as principal component analysis (PCA) and partial least squares (PLS) in the spectroscopic and imaging analysis of organic and biological materials has led to a great increase in the interest of MVA processing of TOF-SIMS data. However, there is still a need to better understand what data to use to answer a given question, how to optimally process the data before applying MVA, and how to correctly interpret the MVA results. The challenges of TOF-SIMS data interpretation will only get more complex, especially for biological samples, further increasing the need for well-controlled MVA methodologies. (c) 2006 Elsevier B.V. All rights reserved.