Multivariate analysis of the 3D cell sequence was conducted using SIMCA 16 (Umetrics Sartorius Stedim, Umeå, Sweden). The data matrices were mean-centered and scaled to unit variance for data exploration using an embedded principal component analysis module (PCA-X) and for data analysis with supervised models. PCA-X score plots and loadings were used to compare analytical quality and overall data structure of both setups. Due to the high sample-tosample variability of the spheroids relative to biological responses, lipidomic profiles were investigated using Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) . Lipids with CVQC < 10% were used to build OPLS-DA models. Shifts associated with exposure were compared between naive and resistant cells using shared-and-unique structure (SUS) plots.