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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
Weijs, L.; Yang, R.S.H.; Das, K.; Covaci, A.; Blust, R. (2013). 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. Environ. Sci. Technol. 47(9): 4365-4374. http://dx.doi.org/10.1021/es400386a
In: Environmental Science and Technology. American Chemical Society: Easton. ISSN 0013-936X; e-ISSN 1520-5851, more
Peer reviewed article  
Available in  Authors 
Keywords
    Aquatic organisms > Marine organisms > Aquatic mammals > Marine mammals
    Models
    Phocoena phocoena (Linnaeus, 1758) [WoRMS]
    Marine/Coastal
Author keywords
    Polybrominated Diphenyl Ethers; Phocoena phocoena; Lifetime Exposure; North Sea; Polychlorinated Biphenyls; Black Sea; Metabolism; Rats; Bioaccumulation; Contaminants
Authors  Top 
  • Weijs, L., more
  • Yang, R.S.H.
  • Das, K., more
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.
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