Major depression, affecting an estimated 350 million people worldwide, poses a serious social and economic threat to modern societies. There are currently two major problems calling for innovative research approaches, namely, the absence of biomarkers predicting antidepressant response and the lack of conceptually novel antidepressant compounds. Both, biomarker predicting a priori whether an individual patient will respond to the treatment of choice as well as an early distinction of responders and nonresponders during antidepressant therapy can have a significant impact on improving this situation. Biosignatures predicting antidepressant response a priori or early in treatment would enable an evidence-based decision making on available treatment options. However, research to date does not identify any biologic or genetic predictors of sufficient clinical utility to inform the selection of specific antidepressant compound for an individual patient. In this review, we propose an optimized translational research strategy to overcome some of the major limitations in biomarker discovery. We are confident that early transfer and integration of data between both species, ideally leading to mutual supportive evidence from both preclinical and clinical studies, are most suitable to address some of the obstacles of current depression research.