COMPUTATIONAL APPROACHES IN TOXICOLOGY AND PHARMACOLOGY: ADVANCING CHEMICAL HAZARD PRIORITIZATION, INTERVENTION, AND CHARACTERIZATION

Abstract

This dissertation develops computational approaches to address complementary challenges in toxicology and pharmacology spanning hazard prioritization, intervention discovery, and hazard characterization. Project I establishes an anticipatory framework for chemical hazard prioritization using data-driven models applied to under-characterized chemical space. Project II develops a computational strategy for prioritizing antidote candidates under experimental constraints by integrating efficacy, central nervous system accessibility, and synthetic feasibility. Project III establishes an integrated modeling framework for microcystin-LR hazard characterization that links external exposure to internal dose metrics to support crossspecies interpretation relevant to human safety. Collectively, this work illustrates how computational approaches can support forward-looking, decision-relevant toxicological assessment across the chemical life cycle