At the single-cell level in conjunction with data-pattern analysis, high-content screening by image analysis or flow cytometry of clinical cell- or tissue-section samples provides differential molecular profiles for the personalized prediction of therapy-dependent disease progression in patients. The molecular reverse-engineering of these molecular profiles, which is the exploration of molecular pathways, backwards, to the origin of the observed molecular differentials, by systems biology has the potential to detect new drug targets in knowledge spaces, typically inaccessible to traditional hypotheses. Furthermore, predictive medicine, by cytomics in stratified patient groups, opens a new way for personalized (or individualized) medicine, as well as for the early detection of adverse drug reactions in patients.