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

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.