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.

Responsible contact

Responsible organization

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).