While for other complex disorders like cancer a limited number of markers are at hand, there are currently no biomarkers available for major depression. A major goal is therefore the identification of biomarkers that can categorize subsets of patients in a consistent manner. Biomarkers for mood disorders provides discovery strategies from scientists in academia and pharma and biotech industries. This will allow a more precise definition of psychiatric disorders and in turn facilitate investigations of the pathophysiology and enhance the ability for patient treatment. Moreover, pharmacogenomics is a new area of medicine that uses the data emerging from the sequencing of the human genome to predict drug responses and to identify new targets for treatment. Pharmacogenomics is of particular relevance to depression, which is a common and complex disorder of unknown cause for which prediction of treatment response and identification of new targets for therapeutics is of crucial importance. Depression represents major health problems in the 21 st century, and is major causes of disability. The fundamental biological mechanisms underlying the effects of psychopharmacological treatments are unknown. Pharmacogenomic approaches to psychiatric disorders offer the possibility to identify a network of genes that may underlie the mechanisms of psychotropic drugs, and the possibility of identifying groups of individuals who are more likely to respond to specific drugs or to suffer from side effects. Such efforts will lead to novel therapeutic targets for drug development and to the individualization of treatment, maximizing the likelihood of positive therapeutic outcomes. In this paper we review studies that has been focused on the prediction of antidepressants response based on genotype. We will also address the methodological issues that are emerging in the context of clinical pharmacogenomic and biomarker's investigation.