Unlock the power of Pred-hERG: the state-of-the-art tool employing machine learning to identify hERG channel blockage and mitigate the potential for cardiac toxicity

Fast, reliable, and user-friendly tool that incorporates multiple QSAR models developed with in vitro, in chemico, and in vivo data, integrated into a consensus Bayesian model that predicts human effects of skin sensitization potential of chemicals.

Innovative and comprehensive workflow for data curation, QSAR modeling, virtual screening and mechanistic interpretations, using an interactive and user-friendly Streamlit dashboard, for computational toxicology and drug discovery projects.

Advancing Safety Assessment with AI-QSAR Models for Predicting Cytotoxicity of Novel Drug Candidates

Predict odorant molecules with explainable AI