Dr. Todor Antonijevic is a toxicologist, physicist, and mechanical engineer in the Houston, Texas, office of the Center for 21st Century Toxicology. He has seven years of experience specializing in computational toxicology, machine learning, and nanomaterials.
He implemented a novel quantitative analytical model to predict a chemically specific critical concentration (“toxicological tipping point”) as a threshold in biological systems between adaptation and adversity from time-course concentration-response high-throughput screening (HTS) data. Dr. Antonijevic uses pharmacokinetics (PBPK) modeling—precisely, quantitative in vitro–to–in vivo extrapolation (qIVIVE)—to translate critical phenomena at a cellular level to apical outcomes and to compare these results with subchronic, repeat-dose animal studies.
Dr. Antonijevic integrated machine learning and qIVIVE to predict hepatotoxicants by developing a new approach to connect high-content imaging (HCI) concentration-response data to adverse hepatic effects observed in animal studies. He also developed a new machine learning algorithm to infer Boolean network responses from multidimensional concentration- and time-course-dependent RNA-seq and HCI data following chemical treatments.
He obtained his Ph.D. in Nanoscience from the University of North Carolina at Greensboro, where he studied phase transition in low-density lipoproteins (LDLs) by applying molecular dynamics analysis and Metropolis Monte Carlo simulations.