Updated publication reference for PubMed record(s): 29226804. In individuals, heterogeneous drug response phenotypes result from a complex interplay of dose, drug specificity, genetic background, and environmental factors, thus challenging our understanding of the underlying processes and optimal use of drugs in the clinic. Here, we use mass spectrometry-based quantification of molecular response phenotypes and logic modeling to explain drug response differences in a panel of cell lines. We apply this approach to cellular cholesterol regulation, a biological process with high clinical relevance. From the quantified molecular phenotypes elicited by various targeted pharmacologic or genetic treatments, we generated cell-line-specific models that quantified the processes beneath the idiotypic intracellular drug responses. The models revealed that in addition to drug uptake and metabolism further cellular processes displayed significant pharmacodynamic response variability between the cell lines, resulting in cell-line-specific drug response phenotypes. This study demonstrates the importance of integrating different types of quantitative systems-level molecular measurements with modeling to understand the effect of pharmacological perturbations on complex biological processes.