Development of PK- and PBPK-based modeling tools for derivation of biomonitoring guidance values.

There are numerous programs ongoing to analyze environmental exposure of humans to xenobiotic chemicals via biomonitoring measurements (e.g.: EU ESBIO, COPHES; US CDC NHANES; Canadian Health Measures Survey). The goal of these projects is to determine relative trends in exposure to chemicals, across time and subpopulations. Due to the lack of data, there is often little information correlating biomarker concentrations with exposure levels and durations. As a result, it can be difficult to utilize biomonitoring data to evaluate if exposures adhere to or exceed hazard/exposure criteria such as the Derived No-Effect Level values under the EU REACH program, or Reference Dose/Concentration values of the US EPA. A tiered approach of simple, arithmetic pharmacokinetic (PK) models, as well as more standardized mean-value, physiologically-based (PBPK) models, have therefore been developed to estimate exposures from biomonitoring results. Both model types utilize a user-friendly Excel spreadsheet interface. QSPR estimations of chemical-specific parameters have been included, as well as accommodation of variations in urine production. Validation of each model's structure by simulations of published datasets and the impact of assumptions of major model parameters will be presented.

Physiologically based pharmacokinetic modelling of human exposure to 2-butoxyethanol.

A physiologically based pharmacokinetic (PBPK) model describing the disposition of 2-butoxyethanol (2-BE) was developed in order to predict the urinary concentration of its major metabolite, butoxyacetic acid (BAA) under a range of exposure scenarios. Based on Corley et al. [Corley, R.A., Bormett, G.A., Ghanayem, B.I., 1994. Physiologically based pharmacokinetics of 2-butoxyethanol and its major metabolite, 2-butoxyacetic acid, in rats and humans. Toxicol. Appl. Pharmacol. 129, 61-79], the model included such features as multiple entry routes into the body, varying workload conditions, metabolism in the liver and elimination of free BAA in urine by glomerular filtration and acid transport. A bladder compartment simulating the fluctuations in metabolite concentration in urine caused by micturition formed a novel aspect of the model. Good agreement between model predictions and existing experimental data of total BAA levels in the blood and urine over various exposure conditions were observed. The mechanistically based PBPK model allowed comparison of disparate studies and also enabled the prediction of urinary concentrations of BAA post-shift. By calculating the total amount of BAA, any inter-individual variability in conjugation is taken into account. This led us to conclude that a biological monitoring guidance value should be proposed for total rather than free BAA with a value of 250 mmol/mol of creatinine (post-shift), based on an 8h exposure to 25 ppm 2-BE at resting working conditions.

Case Study Part 2: Probabilistic modelling of long-term effects of pesticides on individual breeding success in birds and mammals.

Long term exposure of skylarks to a fictitious insecticide and of wood mice to a fictitious fungicide were modelled probabilistically in a Monte Carlo simulation. Within the same simulation the consequences of exposure to pesticides on reproductive success were modelled using the toxicity-exposure-linking rules developed by R.S. Bennet et al. (2005) and the interspecies extrapolation factors suggested by R. Luttik et al. (2005). We built models to reflect a range of scenarios and as a result were able to show how exposure to pesticide might alter the number of individuals engaged in any given phase of the breeding cycle at any given time and predict the numbers of new adults at the season's end.

Case Study Part 1: How to calculate appropriate deterministic long-term toxicity to exposure ratios (TERs) for birds and mammals.

In the European Union, first-tier assessment of the long-term risk to birds and mammals from pesticides is based on calculation of a deterministic long-term toxicity/exposure ratio (TER(lt)). The ratio is developed from generic herbivores and insectivores and applied to all species. This paper describes two case studies that implement proposed improvements to the way long-term risk is assessed. These refined methods require calculation of a TER for each of five identified phases of reproduction (phase-specific TERs) and use of adjusted No Observed Effect Levels (NOELs) to incorporate variation in species sensitivity to pesticides. They also involve progressive refinement of the exposure estimate so that it applies to particular species, rather than generic indicators, and relates spraying date to onset of reproduction. The effect of using these new methods on the assessment of risk is described. Each refinement did not necessarily alter the calculated TER value in a way that was either predictable or consistent across both case studies. However, use of adjusted NOELs always reduced TERs, and relating spraying date to onset of reproduction increased most phase-specific TERs. The case studies suggested that the current first-tier TER(lt )assessment may underestimate risk in some circumstances and that phase-specific assessments can help identify appropriate risk-reduction measures. The way in which deterministic phase-specific assessments can currently be implemented to enhance first-tier assessment is outlined.