Dr. Yang's research interests are Physiologically Based Pharmacokinetic/Pharmacodynamic (PBPK/PD) Modeling, Biologically Based Dose Response (BBDR) Modeling, Reaction Network Modeling, Chemical Mixture Toxicology, Toxicologic Interactions, Carcinogenesis/ Neuro-Developmental Toxicology, Risk Assessment.
Dr. Yang has extensive experience in toxicology in industry, government, and academia. He established and developed the Quantitative and Computational Toxicology Group at CSU. Dr. Yang believes that the application of computer to toxicology, just as computer applications in our life, will become more and more prevalent. Thus, the development of Virtual Cells, Virtual Organs, Virtual Animals, and Virtual Humans is only the matter of time. In that sense, the CSU Quantitative and Computational Toxicology Group is at the beginning of establishing a new form of "bioinformatics" in that they are building the pieces of the puzzle on the complex biological processes involved in toxicology.
Ph.D. - Toxicology; Entomology, North Carolina State University, 1970M.S. - Toxicology; Entomology, North Carolina State University, 1967B.S. - Biology, National Taiwan University, 1963
Yang, R. S. H. 2018. Toxicology and Risk Assessment of Chemical Mixtures and Multiple Stressors, in Comprehensive Toxicology. 3rd Edition, Vol. 1. General Principles, Ed. D. L. Eaton, Elsevier Ltd., Oxford, England, pp. 489-518.Lin, Z., Jaberi-Douraki, M., He, C., Yang, R. S. H., Fisher, J. W., Riviere, J. E. 2017. Performance Assessment and Translation of Physiologically Based Pharmacokinetic Models from acslX™ to Berkeley Madonna™, MATLAB®, and R language: Oxytetracycline and Gold Nanoparticles as Case Examples. Toxicol. Sci. 158:23-35. DOI: https://doi.org/10.1093/toxsci/kfx070.Yang, R. S. H., Weijs, L., McDougall, R., and Housand, C. 2015. The Application of PBPK Modeling, Bayesian Approach, and the Utilization of Markov Chain Monte Carlo Simulation in Risk Assessment, in Toxicology and Risk Assessment, Eds. Anna M. Fan, Elaine M. Khan, and George V. Alexeeff, Pan Stanford Publishing Pte. Ltd., pp. 264-299.Lehmann, G. M., Luukinen, B., Henning, C., Verner, M-A., Assimon, S. A., LaKind, J. S., McLanahan, E. D., Phillips, L. J., Davis, M. H., Powers, C. M., Hines, E. P., Haddad, S., Longnecker, M. P., Poulsen, M. T., Farrer, D. G., Marchitti, S. A., Tan, Y-M., Sagiv, S. K., Welsh, C., Swartout, J. C., Campbell, Jr., J. L., Foster, W. G., Francis, B. M., Yang, R. S. H., Barnett, J. B., El-Masri, H. A., Fenton, S. E., Simmons, J. E., Tornero-Velez, R. 2014. Improving the risk assessment of lipophilic persistent environmental chemicals in breast milk. Crit. Rev. Toxicol. 44:600-617.Weijs, L., Yang, R. S. H., Das, K., Covaci, A., and Blust, R. 2013. Application of Bayesian population PBPK modeling and Markov Chain Monte Carlo simulation to pesticide kinetics studies in protected marine mammals: DDT, DDE, DDD in harbour porpoises. Environ. Sci. Technol. 47:4365-4374.