SynPred (Data-Driven Molecular Design) is a tool for prediction of drug combination effects in cancer using full-agreement synergy metrics and deep learning. SynPred, which leverages state-of-the-art AI advances, specifically designed ensembles of ML and DL algorithms to link in an interdisciplinary approach omics and biophysical traits to predict anticancer drug synergy.