Physiologically based pharmacokinetic modeling of zinc oxide nanoparticles and zinc nitrate in mice - Chen WY (Dove Medical Press, 2015)
Wei-Yu Chen,1 Yi-Hsien Cheng,2 Nan-Hung Hsieh,3 Bo-Chun Wu,2 Wei-Chun Chou,4 Chia-Chi Ho,4 Jen-Kun Chen,5 Chung-Min Liao,2,* Pinpin Lin4,* 1Department of Biomedical Science and Environmental Biology, Kaohsiung Medical University, Kaohsiung, 2Department of Bioenvironmental Systems Engineering, National Taiwan University, Taipei, 3Institute of Labor, Occupational Safety and Health, Ministry of Labor, New Taipei City, 4National Institute of Environmental Health Sciences, 5Institute of Biomedical Engineering and Nanomedicine, National Health Research Institutes, Zhunan, Taiwan *These authors contributed equally to this work Abstract: Zinc oxide nanoparticles (ZnO NPs) have been widely used in consumer products, therapeutic agents, and drug delivery systems. However, the fate and behavior of ZnO NPs in living organisms are not well described. The purpose of this study was to develop a physiologically based pharmacokinetic model to describe the dynamic interactions of 65ZnO NPs in mice. We estimated key physicochemical parameters of partition coefficients and excretion or elimination rates, based on our previously published data quantifying the biodistributions of 10 nm and 71 nm 65ZnO NPs and zinc nitrate (65Zn(NO3)2) in various mice tissues. The time-dependent partition coefficients and excretion or elimination rates were used to construct our physiologically based pharmacokinetic model. In general, tissue partition coefficients of 65ZnO NPs were greater than those of 65Zn(NO3)2, particularly the lung partition coefficient of 10 nm 65ZnO NPs. Sensitivity analysis revealed that 71 nm 65ZnO NPs and 65Zn(NO3)2 were sensitive to excretion and elimination rates in the liver and gastrointestinal tract. Although the partition coefficient of the brain was relative low, it increased time-dependently for 65ZnO NPs and 65Zn(NO3)2. The simulation of 65Zn(NO3)2 was well fitted with the experimental data. However, replacing partition coefficients of 65ZnO NPs with those of 65Zn(NO3)2 after day 7 greatly improved the fitness of simulation, suggesting that ZnO NPs might decompose to zinc ion after day 7. In this study, we successfully established a potentially predictive dynamic model for slowly decomposed NPs. More caution is suggested for exposure to 65ZnO NPs <10 nm because those small 65ZnO NPs tend to accumulate in the body for a relatively longer time than 71 nm 65ZnO NPs and 65Zn(NO3)2 do. Keywords: zinc nanomaterials, bioaccumulation, biodistribution, PBPK modeling, partition coefficient