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.
Preto, A.J.; Matos-Filipe, P.; Mourão, J.; Moreira, A.I.S. SynPred: Prediction of Drug Combination Effects in Cancer using Full-Agreement Synergy Metrics and Deep Learning. Preprints 2021, 2021040395 (doi: 10.20944/preprints202104.0395.v1).