Layla Hosseini-Gerami

This study uses SAFEPATH to identify a novel sphingolipid metabolism mechanism of Gefitinib toxicity and validate it experimentally, while recovering the known UGT1A1-mediated toxicity of Erlotinib.

This paper develops a machine learning model to predict drug-induced liver injury by integrating in vitro and in vivo data with chemical features, achieving improved detection and human-specific sensitivity.

This study develops public classifiers for predicting drug-induced cardiotoxicity using FDA DICTrank data, identifying key chemical and biological features that distinguish toxic from non-toxic compounds.

MAVEN is an R/Shiny app that predicts drug targets and visualizes compound mechanisms of action using transcriptomics and chemical structure data, enabling hypothesis generation for wet-lab scientists.