Background Cadmium is a widespread environmental pollutant that has been shown to exert toxic effects on kidney and bones in humans after long-term exposure. Urinary cadmium concentration is considered a good biomarker of accumulated cadmium in kidney, and diet is the main source of cadmium among nonsmokers. Objective Modeling the link between urinary cadmium and dietary cadmium intake is a key step in the risk assessment of long-term cadmium exposure. There is, however, little knowledge on how this link may vary, especially for susceptible population strata. Methods We used a large population-based study (the Swedish Mammography Cohort), with repeated dietary intake data covering a period of 20 years, to compare estimated dietary cadmium intake with urinary cadmium concentrations on an individual basis. A modified version of the Nordberg-Kjellström model and a one-compartment model were evaluated in terms of their predictions of urinary cadmium. We integrated the models and quantified the between-person variability of cadmium half-life in the population. Finally, sensitivity analyses and Monte Carlo simulations were performed to illustrate how the latter model could serve as a robust tool supporting the risk assessment of cadmium in humans. Results The one-compartment population model appeared to be an adequate modeling option to link cadmium intake to urinary cadmium and to describe the population variability. We estimated the cadmium half-life to be about 11.6 years, with about 25% population variability. Conclusions Population toxicokinetic models can be robust and useful tools for risk assessment of chemicals, because they allow quantification and integration of population variability in toxicokinetics.

Nanoparticles' health risks depend on their biodistribution in the body. Phagocytosis may greatly affect this distribution but has not yet explicitly accounted for in whole body pharmacokinetic models. Here, we present a physiologically based pharmacokinetic model that includes phagocytosis of nanoparticles to explore the biodistribution of intravenously injected polyethylene glycol-coated polyacrylamide nanoparticles in rats. The model explains 97% of the observed variation in nanoparticles amounts across organs. According to the model, phagocytizing cells quickly capture nanoparticles until their saturation and thereby constitute a major reservoir in richly perfused organs (spleen, liver, bone marrow, lungs, heart and kidneys), storing 83% of the nanoparticles found in these organs 120 h after injection. Key determinants of the nanoparticles biodistribution are the uptake capacities of phagocytizing cells in organs, the partitioning between tissue and blood, and the permeability between capillary blood and tissues. This framework can be extended to other types of nanoparticles by adapting these determinants.

To assess the potential toxicity of nanoparticles (NPs), information concerning their uptake and disposition (biokinetics) is essential. Experience with industrial chemicals and pharmaceutical drugs reveals that biokinetics can be described and predicted accurately by physiologically-based pharmacokinetic (PBPK) modeling. The nano PBPK models developed to date all concern a single type of NP. Our aim here was to extend a recent model for pegylated polyacrylamide NP in order to develop a more general PBPK model for nondegradable NPs injected intravenously into rats. The same model and physiological parameters were applied to pegylated polyacrylamide, uncoated polyacrylamide, gold, and titanium dioxide NPs, whereas NP-specific parameters were chosen on the basis of the best fit to the experimental time-courses of NP accumulation in various tissues. Our model describes the biokinetic behavior of all four types of NPs adequately, despite extensive differences in this behavior as well as in their physicochemical properties. In addition, this simulation demonstrated that the dose exerts a profound impact on the biokinetics, since saturation of the phagocytic cells at higher doses becomes a major limiting step. The fitted model parameters that were most dependent on NP type included the blood:tissue coefficients of permeability and the rate constant for phagocytic uptake. Since only four types of NPs with several differences in characteristics (dose, size, charge, shape, and surface properties) were used, the relationship between these characteristics and the NPdependent model parameters could not be elucidated and more experimental data are required in this context. In this connection, intravenous biodistribution studies with associated PBPK analyses would provide the most insight.

Physiologically based pharmacokinetic (PBPK) models are used in mode-of-action based risk and safety assessments to estimate internal dosimetry in animals and humans. When used in risk assessment, these models can provide a basis for extrapolating between species, doses, and exposure routes or for justifying nondefault values for uncertainty factors. Characterization of uncertainty and variability is increasingly recognized as important for risk assessment; this represents a continuing challenge for both PBPK modelers and users. Current practices show significant progress in specifying deterministic biological models and nondeterministic (often statistical) models, estimating parameters using diverse data sets from multiple sources, using them to make predictions, and characterizing uncertainty and variability of model parameters and predictions. The International Workshop on Uncertainty and Variability in PBPK Models, held 31 Oct-2 Nov 2006, identified the state-of-the-science, needed changes in practice and implementation, and research priorities. For the short term, these include (1) multidisciplinary teams to integrate deterministic and nondeterministic/statistical models; (2) broader use of sensitivity analyses, including for structural and global (rather than local) parameter changes; and (3) enhanced transparency and reproducibility through improved documentation of model structure(s), parameter values, sensitivity and other analyses, and supporting, discrepant, or excluded data. Longer-term needs include (1) theoretical and practical methodological improvements for nondeterministic/statistical modeling; (2) better methods for evaluating alternative model structures; (3) peer-reviewed databases of parameters and covariates, and their distributions; (4) expanded coverage of PBPK models across chemicals with different properties; and (5) training and reference materials, such as cases studies, bibliographies/glossaries, model repositories, and enhanced software. The multidisciplinary dialogue initiated by this Workshop will foster the collaboration, research, data collection, and training necessary to make characterizing uncertainty and variability a standard practice in PBPK modeling and risk assessment.

Perfluorinated alkyl acids (PFAA) are highly persistent and bioaccumulative and have been associated with several adverse health effects. The chemical structure mainly differs in two ways: the length of the hydrophobic alkyl chain and the type of hydrophilic end group. Little is known how the chemical structure affects the toxicokinetics (TK) in different organisms. We studied the TK of four PFAA (PFOS, PFHxS, PFOA, and PFBA) with different chain lengths (4–8 carbons) and functional groups (sulfonic and carboxylic acid) in zebrafish (Danio rerio) embryo. The time courses of the external (ambient water) and internal concentrations were determined at three exposure concentrations from 2 up to 120 h postfertilization (hpf). Three of the four PFAA showed a biphasic uptake pattern with slow uptake before hatching (around 48 hpf) and faster uptake thereafter. A two-compartment TK model adequately described the biphasic uptake pattern, suggesting that the chorion functions as an uptake barrier until 48 hpf. The bioconcentration factors (BCF) determined at 120 hpf varied widely between PFAA with averages of approximately 4000 (PFOS), 200 (PFHxS), 50 (PFOA), and 0.8 (PFBA) L kg dry weight–1, suggesting that both the alkyl chain length and the functional group influence the TK. The differences in toxic potency were reduced by 3 orders of magnitude when comparing internal effect concentrations instead of effective external concentrations.