While quantitative estimates of risk have been a standard practice in cancer risk assessment for many years, no similar practice is evident in noncancer risk assessment. We use two recent examples involving methylmercury and arsenic to illustrate the negative impact of this discrepancy on risk communication and cost‐benefit analysis. We argue for a more balanced treatment of cancer and noncancer risks and suggest an approach for reaching this goal.
A Bayesian approach, implemented using Markov Chain Monte Carlo (MCMC) analysis, was applied with a physiologically‐based pharmacokinetic (PBPK) model of methylmercury (MeHg) to evaluate the variability of MeHg exposure in women of childbearing age in the U.S. population. The analysis made use of the newly available National Health and Nutrition Survey (NHANES) blood and hair mercury concentration data for women of age 16–49 years (sample size, 1,582). Bayesian analysis was performed to estimate the population variability in MeHg exposure (daily ingestion rate) implied by the variation in blood and hair concentrations of mercury in the NHANES database. The measured variability in the NHANES blood and hair data represents the result of a process that includes interindividual variation in exposure to MeHg and interindividual variation in the pharmacokinetics (distribution, clearance) of MeHg. The PBPK model includes a number of pharmacokinetic parameters (e.g., tissue volumes, partition coefficients, rate constants for metabolism and elimination) that can vary from individual to individual within the subpopulation of interest. Using MCMC analysis, it was possible to combine prior distributions of the PBPK model parameters with the NHANES blood and hair data, as well as with kinetic data from controlled human exposures to MeHg, to derive posterior distributions that refine the estimates of both the population exposure distribution and the pharmacokinetic parameters. In general, based on the populations surveyed by NHANES, the results of the MCMC analysis indicate that a small fraction, less than 1%, of the U.S. population of women of childbearing age may have mercury exposures greater than the EPA RfD for MeHg of 0.1 μg/kgg/day, and that there are few, if any, exposures greater than the ATSDR MRL of 0.3 μgg/kgg/day. The analysis also indicates that typical exposures may be greater than previously estimated from food consumption surveys, but that the variability in exposure within the population of U.S. women of childbearing age may be less than previously assumed.
An occupational risk assessment for manganese (Mn) was performed based on benchmark dose analysis of data from two epidemiological studies providing dose‐response information regarding the potential neurological effects of exposure to airborne Mn below the current Occupational Safety and Health Administration (OSHA) Permissible Exposure Level (PEL) of 5 mg Mn/m3. Based on a review of the scientific evidence regarding the toxicity of Mn, it was determined that the most appropriate measure of exposure to airborne Mn for the subclinical effects measured in these studies is recent (rather than historical or cumulative) concentration of Mn in respirable (rather than total) particulate. For each of the studies analyzed, the individual exposure and response data from the original study had been made available by the investigators. From these two studies benchmark concentrations calculated for eight endpoints ranged from 0.09 to 0.27 mg Mn/m3. From our evaluation of these results, and considering the fact that the subtle, subclinical effects represented by the neurological endpoints tested in these studies do not represent material impairment, we believe an appropriate occupational exposure guideline for manganese would be in the range of 0.1 to 0.3 mg Mn/m3, based on the respirable particulate fraction only, and expressed as an 8‐hour time‐weighted average.
The approximate solution of the two‐stage clonal expansion model of cancer may substantially deviate from the exact solution, and may therefore lead to erroneous conclusions in particular applications. However, for time‐varying parameters the exact solution (method of characteristics) is not easy to implement, hampering the accessibility of the model to nonmathematicians. Based on intuitive reasoning, Clewell et al. (1995) proposed an improved approximate solution that is easy to implement whatever time‐varying behavior the parameters may have. Here we provide the mathematical foundation for the approximation suggested by Clewell et al. (1995) and show that, after a slight modification, it is in fact an exact solution for the case of time‐constant parameters. We were not able to prove that it is an exact solution for time‐varying parameters as well. However, several computer simulations showed that the numerical results do not differ from the exact solution as proposed by Moolgavkar and Luebeck (1990). The advantage of this alternative solution is that the hazard rate of the first malignant cell can be evaluated by numerically integrating a single differential equation.
Abstractβ‐Chloroprene is used in the production of polychloroprene, a synthetic rubber. In 2010, Environmental Protection Agency (EPA) published the Integrated Risk Information System "Toxicological Review of Chloroprene," concluding that chloroprene was "likely to be carcinogenic to humans." This was based on findings from a 1998 National Toxicology Program (NTP) study showing multiple tumors within and across animal species; results from occupational epidemiological studies; a proposed mutagenic mode of action; and structural similarities with 1,3‐butadiene and vinyl chloride. Using mouse data from the NTP study and assuming a mutagenic mode of action, EPA calculated an inhalation unit risk (IUR) for chloroprene of 5 × 10−4 per µg/m3. This is among the highest IURs for chemicals classified by IARC or EPA as known or probable human carcinogens and orders of magnitude higher than the IURs for carcinogens such as vinyl chloride, benzene, and 1,3‐butadiene. Due to differences in pharmacokinetics, mice appear to be uniquely responsive to chloroprene exposure compared to other animals, including humans, which is consistent with the lack of evidence of carcinogenicity in robust occupational epidemiological studies. We evaluated and integrated all lines of evidence for chloroprene carcinogenicity to assess whether the 2010 EPA IUR could be scientifically substantiated. Due to clear interspecies differences in carcinogenic response to chloroprene, we applied a physiologically based pharmacokinetic model for chloroprene to calculate a species‐specific internal dose (amount metabolized/gram of lung tissue) and derived an IUR that is over 100‐fold lower than the 2010 EPA IUR. Therefore, we recommend that EPA's IUR be updated.
The risk of human exposure to total chlorotriazines (TCT) in drinking water was evaluated using a physiologically based pharmacokinetic (PBPK) model. Daily TCT (atrazine, deethylatrazine, deisopropylatrazine, and diaminochlorotriazine) chemographs were constructed for 17 frequently monitored community water systems (CWSs) using linear interpolation and Krieg estimates between observed TCT values. Synthetic chemographs were created using a conservative bias factor of 3 to generate intervening peaks between measured values. Drinking water consumption records from 24-h diaries were used to calculate daily exposure. Plasma TCT concentrations were updated every 30 minutes using the PBPK model output for each simulated calendar year from 2006 to 2010. Margins of exposure (MOEs) were calculated (MOE = [Human Plasma TCTPOD] ÷ [Human Plasma TCTEXP]) based on the toxicological point of departure (POD) and the drinking water-derived exposure to TCT. MOEs were determined based on 1, 2, 3, 4, 7, 14, 28, or 90 days of rolling average exposures and plasma TCT Cmax, or the area under the curve (AUC). Distributions of MOE were determined and the 99.9th percentile was used for risk assessment. MOEs for all 17 CWSs were >1000 at the 99.9th percentile. The 99.9th percentile of the MOE distribution was 2.8-fold less when the 3-fold synthetic chemograph bias factor was used. MOEs were insensitive to interpolation method, the consumer's age, the water consumption database used and the duration of time over which the rolling average plasma TCT was calculated, for up to 90 days. MOEs were sensitive to factors that modified the toxicological, or hyphenated appropriately no-observed-effects level (NOEL), including rat strain, endpoint used, method of calculating the NOEL, and the pharmacokinetics of elimination, as well as the magnitude of exposure (CWS, calendar year, and use of bias factors).
An analysis of the uncertainty in guidelines for the ingestion of methylmercury (MeHg) due to human pharmacokinetic variability was conducted using a physiologically based pharmacokinetic (PBPK) model that describes MeHg kinetics in the pregnant human and fetus. Two alternative derivations of an ingestion guideline for MeHg were considered: the U.S. Environmental Protection Agency reference dose (RfD) of 0.1 pg/kg/day derived from studies of an Iraqi grain poisoning episode, and the Agency for Toxic Substances and Disease Registry chronic oral minimal risk level (MRL) of 0.5 pglkglday based on studies of a fisheating population in the Seychelles Islands. Calculation of an ingestion guideline for MeHg from either of these epidemiological studies requires calculation of a dose conversion factor (DCF) relating a hair mercury concentration to a chronic MeHg ingestion rate. To evaluate the uncertainty in this DCF across the population of U.S. women of child‐bearing age, Monte Carlo analyses were performed in which distributions for each of the parameters in the PBPK model were randomly sampled lo00 times. The 1st and 5th percentiles of the resulting distribution of DCFs were a factor of 1.8 and 1.5 below the median, respectively. This estimate of variability is consistent with, but somewhat less than, previous analyses performed with empirical, one‐compartment pharmacokinetic models. The use of a consistent factor in both guidelines of 1.5 for pharmacokinetic variability in the DCF, and keeping all other aspects of the derivations unchanged, would result in an RfD of 0.2 pglkglday and an MRL of 0.3 pglkglday.
