title: Application of Bayesian population physiologically based pharmacokinetic (PBPK) modeling and Markov chain Monte Carlo simulations to pesticide kinetics studies in protected marine mammals: DDT, DDE, and DDD in harbor porpoises.
abstract: Physiologically based pharmacokinetic (PBPK) modeling in marine mammals is a challenge because of the lack of parameter information and the ban on exposure experiments. To minimize uncertainty and variability, parameter estimation methods are required for the development of reliable PBPK models. The present study is the first to develop PBPK models for the lifetime bioaccumulation of p,p'-DDT, p,p'-DDE, and p,p'-DDD in harbor porpoises. In addition, this study is also the first to apply the Bayesian approach executed with Markov chain Monte Carlo simulations using two data sets of harbor porpoises from the Black and North Seas. Parameters from the literature were used as priors for the first "model update" using the Black Sea data set, the resulting posterior parameters were then used as priors for the second "model update" using the North Sea data set. As such, PBPK models with parameters specific for harbor porpoises could be strengthened with more robust probability distributions. As the science and biomonitoring effort progress in this area, more data sets will become available to further strengthen and update the parameters in the PBPK models for harbor porpoises as a species anywhere in the world. Further, such an approach could very well be extended to other protected marine mammals.
authors.affiliation: Department of Biology, University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp, Belgium. liesbeth.weijs@ua.ac.be
authors.forename: Liesbeth
authors.initials: L
authors.lastname: Weijs
authors.forename: Raymond S H
authors.initials: RS
authors.lastname: Yang
authors.forename: Krishna
authors.initials: K
authors.lastname: Das
authors.forename: Adrian
authors.initials: A
authors.lastname: Covaci
authors.forename: Ronny
authors.initials: R
authors.lastname: Blust
mesh_terms: D000818:Animals; D001499:Bayes Theorem; D003634:DDT / Q000493:pharmacokinetics; D003633:Dichlorodiphenyl Dichloroethylene / Q000493:pharmacokinetics; D003632:Dichlorodiphenyldichloroethane / Q000493:pharmacokinetics; D008390:Markov Chains; D009010:Monte Carlo Method; D010575:Pesticides / Q000493:pharmacokinetics*; D050741:Phocoena / Q000378:metabolism*; D014874:Water Pollutants, Chemical / Q000493:pharmacokinetics*
chemical_list: D010575:Pesticides; D014874:Water Pollutants, Chemical; D003633:Dichlorodiphenyl Dichloroethylene; D003634:DDT; D003632:Dichlorodiphenyldichloroethane