Lifetime PCB 153 bioaccumulation and pharmacokinetics in pilot whales: Bayesian population PBPK modeling and Markov chain Monte Carlo simulations

• Published in: Chemosphere (Oxford) 2014-01, Vol.94, p.91-96
• Main Authors: Weijs, Liesbeth, Roach, Anthony C., Yang, Raymond S.H., McDougall, Robin, Lyons, Michael, Housand, Conrad, Tibax, Detlef, Manning, Therese, Chapman, John, Edge, Katelyn, Covaci, Adrian, Blust, Ronny
• Format: Article
• Language: English
• Subjects: Animal, plant and microbial ecology; Animals; Applied ecology; Australia; Bayes Theorem; Bayesian; Bioaccumulation; Biological and medical sciences; Ecotoxicology, biological effects of pollution; Effects of pollution and side effects of pesticides on vertebrates; Environmental Exposure - analysis; Environmental Exposure - statistics & numerical data; Fundamental and applied biological sciences. Psychology; Male; Mammalia; Markov Chains; MCMC; Models, Chemical; Monte Carlo Method; PBPK; Pilot whale; Polychlorinated Biphenyls - metabolism; Uncertainty; Water Pollutants, Chemical - metabolism; Water Pollution, Chemical - statistics & numerical data; Whales, Pilot - metabolism
• ISSN: 0045-6535; 1879-1298
• DOI: 10.1016/j.chemosphere.2013.09.019

•PBPK models for wild animals should address model uncertainty and variability.•Bayesian approach and MCMC simulations for reliable parameter estimations.•Models were evaluated with data from long-finned pilot whales from Tasmania.•Model predictions show an overall decrease in PCB 153 levels in male pilot whales. Physiologically based pharmacokinetic (PBPK) models for wild animal populations such as marine mammals typically have a high degree of model uncertainty and variability due to the scarcity of information and the embryonic nature of this field. Parameters values used in marine mammals models are usually taken from other mammalian species (e.g. rats or mice) and might not be entirely suitable to properly explain the kinetics of pollutants in marine mammals. Therefore, several parameters for a PBPK model for the bioaccumulation and pharmacokinetics of PCB 153 in long-finned pilot whales were estimated in the present study using the Bayesian approach executed with Markov chain Monte Carlo (MCMC) simulations. This method uses ‘prior’ information of the parameters, either from the literature or from previous model runs. The advantage is that this method uses such ‘prior’ parameters to calculate probability distributions to determine ‘posterior’ values that best explain the field observations. Those field observations or datasets were PCB 153 concentrations in blubber of long-finned pilot whales from Sandy Cape and Stanley, Tasmania, Australia. The model predictions showed an overall decrease in PCB 153 levels in blubber over the lifetime of the pilot whales. All parameters from the Sandy Cape model were updated using the Stanley dataset, except for the concentration of PCB 153 in the milk. The model presented here is a promising and preliminary start to PBPK modeling in long-finned pilot whales that would provide a basis for non-invasive studies in these protected marine mammals.