Dataset Information

PBPK-Based Probabilistic Risk Assessment for Total Chlorotriazines in Drinking Water.

ABSTRACT: 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 99.9(th)percentile. The 99.9(th)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).

SUBMITTER: Breckenridge CB

PROVIDER: S-EPMC4809455 | biostudies-literature | 2016 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

PBPK-Based Probabilistic Risk Assessment for Total Chlorotriazines in Drinking Water.

Breckenridge Charles B CB Campbell Jerry L JL Clewell Harvey J HJ Andersen Melvin E ME Valdez-Flores Ciriaco C Sielken Robert L RL

Toxicological sciences : an official journal of the Society of Toxicology 20160121 2

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 pea ...[more]

PMID: 26794141

Similar Datasets

Project description:BackgroundExtensive exposure to per- and polyfluoroalkyl substances (PFAS) have been observed in many countries. Current deterministic frameworks for risk assessment lack the ability to predict the likelihood of effects and to assess uncertainty. When exposure exceeds tolerable intake levels, these shortcomings hamper risk management and communication.ObjectiveThe integrated probabilistic risk assessment (IPRA) combines dose-response and exposure data to estimate the likelihood of adverse effects. We evaluated the usefulness of the IPRA for risk characterization related to decreased levels of total triiodothyronine (T3) in humans following a real case of high exposure to PFAS via drinking water.MethodsPFAS exposure was defined as serum levels from residents of a contaminated area in Ronneby, Sweden. Median levels were 270 ng/mL [perfluorooctane sulfonic acid (PFOS)] and 229 ng/mL [perfluorohexane sulfonic acid (PFHxS)] for individuals who resided in Ronneby 1 y before the exposure termination. This data was integrated with data from a subchronic toxicity study in monkeys exposed daily to PFOS. Benchmark dose modeling was employed to describe separate dose-effect relationship for males and females, and extrapolation factor distributions were used to estimate the corresponding human benchmark dose. The critical effect level was defined as a 10% decrease in total T3.ResultsThe median probability of critical exposure, following a combined exposure to PFOS and PFHxS, was estimated to be [2.1% (90% CI: 0.4%-13.1%)]. Gender-based analysis showed that this risk was almost entirely distributed among women, namely [3.9% (90% CI: 0.8%-21.6%)].DiscussionThe IPRA was compared with the traditional deterministic Margin of Exposure (MoE) approach. We conclude that probabilistic risk characterization represents an important step forward in the ability to adequately analyze group-specific health risks. Moreover, quantifying the sources of uncertainty is desirable, as it improves the awareness among stakeholders and will guide future efforts to improve accuracy. https://doi.org/10.1289/EHP6654.

Project description:Water plays a major role in supporting the wellness and life processes in living things as well as in the ecological structure's stabilities. However, several environmental scientists have recounted the alarming menace unfit water quality portends as well as the shortfalls of its global utilization in various spheres of life. This study aims to determine the fitness of the Ossiomo River and its likely health risk impact when consumed or used for other domestic purposes. The outcome of the physicochemical and heavy metal characterization showed that most of the parameters surpassed the slated benchmarks. Findings from the study revealed a significant difference (p < 0.05) for water temperature, color, TDS, BOD5, HCO3, Na, Fe, Mn, and THC across the four stations respectively. Meanwhile, pH, salinity, turbidity, TSS, DO, Cl, P, NH4H, NO2, NO3, SO4, Zn, Cu, Cr, Ni, Pb, and V showed no significant (p > 0.05) across the four stations respectively. The pH level of the water was slightly acidic at the range of 4.40-6.82. The outcome of the computed water quality index showed that station 1 (66.38) was poor for human ingestion which was above the set slated benchmarks of 26-50. However, stations 2-4 (163.79, 161.79, and 129.95) were unsuitable for drinking which was above the set slated benchmarks of 100. The outcome of the health risk evaluation revealed that the hazard quotients (HQs) were considered greater than 1 (>1) for Cr (2.55). The hazard index (0.46) via the dermal pathway was <1 while the ingestion (4.35) pathway was >1. The sum of the HQs (4.81) was also > 1. Thus, there are possible non-carcinogenic health risks via direct ingestion of the water. The outcome from the carcinogenic risk for Pb, Cr, and Cd (6 × 10-3, 4.00 × 10-1, and 1.22 × 100), was somewhat greater than the target goal (1.0 × 10-6 to 1.0 × 10-4) of carcinogenic risks stipulated by the United States Environmental Protection Agency for drinking water, respectively, especially for Cd. There might be a potential carcinogenic risk if the water is consumed when the metal contents are higher than the target limits set. Sustainable farming and treatment of wastes from industrial outputs should be the main management of this watercourse.

Project description:Despite the relative prosperity of Scandinavian countries, contamination of the drinking water supply with parasites has occurred on various occasions in the last few decades. These events have resulted in outbreaks of disease involving several thousand cases and/or the necessity for implementation of boil-water advisories. Against this background, in 2008, and again in 2019, the Norwegian Food Safety Authority requested a risk assessment from an independent scientific body regarding parasites in Norwegian drinking water. On each occasion, it was requested that specific questions were addressed. For the first assessment, data, both of general relevance and specific for Norway, were collected from appropriate sources, as available. Based on some of this information, a quantitative probability model was established and run to estimate the number of cases of waterborne cryptosporidiosis and giardiasis that may be expected in Norway, both in the general public and the immunocompromised, and under conditions where water treatment should be optimal, and also when water treatment efficacy may be compromised by weather conditions. For the second assessment, approximately a decade after the first, an update on the previous assessment was requested. Differences in information availability and other changes between the two assessments were described; although more data were available at the second assessment, considerable gaps still remained. For both assessments, data on the occurrence of these parasites in the Norwegian population, particularly those infected in Norway, were considered a challenge. However, due to changes in reporting requirements in 2020, the situation was improved for the second assessment. In addition, data were lacking for both assessments on whether animals or humans are most likely to contaminate water sources, and the species and genotypes of these parasites in Norwegian animals. It was also noted that some of the newer data on parasite numbers detected in water samples should be treated with caution. Due to this, further modelling was not conducted. The relevance of risk-based sampling rather than ad hoc sampling of water sources was also addressed. Despite the data gaps, this article provides an overview of the opportunities provided by conducting such assessments. In addition, some of the challenges encountered in attempting to estimate the risk posed from parasite contamination of water sources in Norway, particularly under predicted conditions of climate change, are described.

Dataset Information

PBPK-Based Probabilistic Risk Assessment for Total Chlorotriazines in Drinking Water.

Publications

PBPK-Based Probabilistic Risk Assessment for Total Chlorotriazines in Drinking Water.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets