James M. Gallo

This paper introduces scPBPK models to study drug disposition at the cellular level, showing heterogeneity in drug concentration using negative binomial distributions for ED processes.

The paper uses multiomic data to identify cell state transitions in GBM and proposes potential drug targets to alter these transitions.

The paper identifies cardiotoxic drug signatures using bulk transcriptomics and integrates them with genomic and single-cell data to predict toxicity mechanisms.

The paper identifies genomic signatures predicting allopurinol and combination therapy responses in lung cancer using TCGA, CCLE, and patient-derived tumor data.