The liver, which plays a critical role in the metabolism of xenobiotics, is highly susceptible to damage from drugs and their metabolites. Thus, there is a demand for an accurate, in silico model for the prediction of drug candidate hepatotoxicity, which would greatly benefit drug development. We developed a drug-induced liver injury (DILI) prediction model trained on a large-scale hepatotoxicity dataset that uses an ensemble strategy. “X-DILiver” can assist successful drug development by accurately predicting the biological safety associated with the hepatotoxicity of drug candidates.
Web server: http://xdiliver.lile.bio