Drug discovery is a challenging multi-objective pro-blem where numerous pharmaceutically important objectives need to be adequately satisfied for a solution to be found. The problem is characterized by vast, complex solution spaces further perplexed by the pre-sence of conflicting objectives. Multi-objective optimi- zation methods, designed specifically to address such problems, have been introduced to the drug discovery field over a decade ago and have steadily gained in acceptance ever since. This paper reviews the latest multi-objective methods and applications reported in the literature, specifically in quantitative structure– activity modeling, docking, de novo design and library design. Further, the paper reports on related develop- ments in drug discovery research and advances in the multi-objective optimization field.