During the past decade, quantitative structure–activity relationship (QSAR) enjoyed an ever-increasing application in various fields including translational sciences. This review summarizes the progress in data preprocessing, processing, and validation techniques as well as the standardization in reporting of QSARs and the legislative framework promoting the use of computational approaches as viable tools for reducing animal testing. Software products focused on prediction of translational end-points and recently published individual models are discussed briefly. Particular attention is given to challenges springing from the immense complexity of translational QSARs.
By Svetoslav Slavov, Richard D. Beger