Mechanistic Biological Modeling for Next-Generation Risk Assessment
Translate environmental exposure into internal and target-tissue dose using PBPK/PBTK, IVIVE/QIVIVE, and human-relevant risk assessment.
Learn morePredictive Computational Toxicology
Predicting how chemicals and nanomaterials move through biological systems.
We integrate mechanistic modeling, quantitative toxicology, and artificial intelligence to connect exposure with internal dose, biological interactions, and health-relevant outcomes.
About Us
At UCR, the Chou Lab develops computational and mechanistic approaches to understand how chemicals, nanomaterials, and therapeutic delivery systems move through biological systems and influence health-relevant outcomes.
Our lab is based in the Department of Environmental Sciences in the College of Natural & Agricultural Sciences at the University of California, Riverside. Dr. Chou is also affiliated with the Environmental Toxicology Graduate Program.
Research Areas
We develop mechanistic and AI-enabled approaches to connect environmental exposure and therapeutic delivery with internal dose, biological interactions, and health-relevant outcomes.
AI-Enabled Predictive Toxicology
Integrate machine learning with mechanistic and experimental evidence to predict toxicokinetics, toxicity, and chemical behavior when data are sparse.
Learn moreNano-Bio Interactions & Nanomedicine
Determine how biological identity and nano-bio interactions control nanoparticle fate, tissue distribution, therapeutic delivery, and off-target exposure.
Learn moreBiomaterials & Regional Drug Delivery
Determine how material properties, release kinetics, and administration strategies shape target-tissue exposure and biological response.
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