Summary
John Wambaugh is a Principal Computational Exposure and Toxicokinetic Research Scientist with nearly two decades of leadership in computational toxicology, exposure science, and high-throughput toxicokinetics. He builds open-source tools and models—like the widely used httk package and SEEM predictors—that enable rapid IVIVE, PBTK simulations, and population variability analyses to inform chemical risk assessment and reduce animal testing. A former EPA research leader and co-founder of ExpoCast, he has translated complex pharmacokinetic and exposure data into actionable regulatory insights while mentoring many trainees and organizing communities of practice. John combines a physics and computer science background with advanced statistics, Bayesian methods, and machine learning to push NAMs from concept to regulatory use. Based in Chapel Hill, he now leads computational exposure research at UL Research Institutes while teaching and supervising NAMs-focused graduate work at UNC. Despite a deep regulatory track record, he still draws on his experimental and algorithmic roots—from building imaging rigs in physics labs to authoring R packages—to solve practical challenges in environmental health.
11 years of coding experience
14 years of employment as a software developer
Ph.D. Physics, Ph.D. Physics at Duke University
M.S. Physics, M.S. Physics at Georgia Institute of Technology
B.S. Physics, B.S. Physics at University of Michigan
English, Russian