APROBA-Plus: A probabilistic tool to evaluate and express uncertainty in hazard characterization and exposure assessment of substances

Reducing uncertainty in dose-response assessments by incorporating Bayesian benchmark dose modeling and in vitro data on population variability

There are two primary sources of uncertainty in the interpretability of toxicity values, like the reference dose (RfD): estimates of the point of departure (POD) and the absence of chemical-specific human variability data. We hypothesize two solutions-employing Bayesian benchmark dose (BBMD) modeling to refine POD determination and combining high-throughput toxicokinetic modeling with population-based toxicodynamic in vitro data to characterize chemical-specific variability. These hypotheses were tested by deriving refined probabilistic estimates for human doses corresponding to a specific effect size (M) in the Ith population percentile (HDM I) across 19 Superfund priority chemicals. HDM I values were further converted to biomonitoring equivalents in blood and urine for benchmarking against human data. Compared to deterministic default-based RfDs, HDM I values were generally more protective, particularly influenced by chemical-specific data on interindividual variability. Incorporating chemical-specific in vitro data improved precision in probabilistic RfDs, with a median 1.4-fold reduction in uncertainty variance. Comparison with US Environmental Protection Agency's Exposure Forecasting exposure predictions and biomonitoring data from the National Health and Nutrition Examination Survey identified chemicals with margins of exposure nearing or below one. Overall, to mitigate uncertainty in regulatory toxicity values and guide chemical risk management, BBMD modeling and chemical-specific population-based human in vitro data are essential.

Integrated evidence of transcriptional, metabolic, and intestinal microbiota changes in Ruditapes philippinarum due to perfluorooctanoic acid-induced immunotoxicity

Perfluorooctanoic acid (PFOA) is a toxic pollutant that bioaccumulates and is a significant public health concern due to its ubiquitous and persistent occurrence in global environments. Few studies have evaluated the adverse effects of PFOA on immune system, and this is particularly true for mollusks. Here, the PFOA-associated effects on immune system were evaluated in Ruditapes philippinarum using integrated analysis of metabolomes, microbiomes, and transcriptomes, providing evidence for possible mechanisms related to immunotoxicity. PFOA exposure caused clear variation in several important metabolites related to immune regulatory function within the haemolyph from R. philippinarum, while also altering key metabolic pathways, including those of lipids, unsaturated fatty acids (UFAs), and bile acids (BAs). After exposure to PFOAs, intestinal bacterial communities also clearly changed, with the predominant microflora becoming Mycoplasma and Bacteroidetes that are related to intestinal inflammation. Molecular analyses provided consistent results, wherein the expression of immune-related genes was significantly altered. Integration of the multi-'omics' analyses suggested that the TLR/MyD88/NF-kB pathway, along with PI3K-Akt-mTOR pathway, PPAR-mediated lipid metabolism and the autophagy signaling pathway, likely play important roles in initiating immunotoxic effects in R. philippinarum after PFOA exposure. These results provide further evidence that PFOA exposure can lead to immunologic dysfunction and also provide new insights into the mechanisms of PFAS alteration of bivalve immune function.

Bayesian-Based Probabilistic Risk Assessment of Fipronil in Food: A Case Study in Taiwan

Fipronil, a broad-spectrum insecticide, is widely used in agriculture and veterinary practices. Fipronil-induced neurotoxicity and potential adverse effects on humans and aquatic organisms have raised health concerns. Monitoring programs have been implemented globally to assess fipronil residues in food, including fruits, vegetables, and animal products. However, previous exposure assessments have often focused on specific food categories or subsets of items, resulting in limited insights into the overall health risks. Additionally, the large number of non-detect fipronil residues in food has introduced uncertainties in exposure assessment. To address these issues, a probabilistic exposure assessment and dose-response analysis were adopted in this study, considering the sample distribution below the detection limit to better characterize uncertainties and population variability in health risk assessments. The estimated fipronil exposure to the general public ranges from 6.38 × 10-6 ± 0.00017 mg/kg/day to 9.83 × 10-6 ± 0.00034 mg/kg/day. Only one out of 200,000 simulated individuals had a fipronil dose exceeding the probabilistic reference dose (0.048 mg/kg/day, pRfD), which aims to protect 99% of the population with effects less than 10% extra risk. By incorporating uncertainties in exposure and dose-response data, a more comprehensive understanding of the health risks associated with fipronil exposure in the Taiwanese population has been achieved.

Quantitative chemical risk assessment for mixtures: Application to alkylphenol mixtures and phthalate mixtures in tap and bottled water

The occurrence and hazard risks of mixtures of Contaminants of Emerging Concern (CECs) in drinking water (DW) lead to serious consideration regarding the possible impacts on public health. Consequently, there is ongoing research, development and empowerment of risk assessment procedures to get more toxicological insight. For instance, alkylphenols and phthalates have been frequently reported to be present both in bottled and tap water, affecting different human endpoints. Currently, deterministic chemical risk assessment (CRA) is used to evaluate the compounds' mixture health risk. However, CRA deals just qualitatively with sources of uncertainty, which may lead to erroneous assessment of risks. Here, a new procedure for quantitative chemical risk assessment of CEC mixtures (QCRA_MIX) is proposed. Its potential is illustrated by a case study where the risks related to the presence of mixtures of alkylphenols or phthalates in tap versus bottled DW are compared. Uncertainties in both exposure and hazard assessment steps of the procedure are included to calculate a probabilistic mixture Benchmark Quotient (BQ_MIX). The QCRA_MIX procedure highlighted the non-negligible health risks posed by those compounds in both DW sources based on overall water consumption. In fact, DW consumers' behaviour in 13 different countries, in terms of total DW consumption and fraction of bottled and tap water consumed, were considered to evaluate the influence on health risk. For alkylphenols, the total water consumption was found to be the most relevant factor in increasing the health risk, while for phthalates the risk was found to be mainly influenced by the percentage of bottled water consumed. Hence, the proposed QCRA_MIX procedure can be a valuable tool for prioritization of CECs to be included in DW regulations which aim to minimize the overall risk, accounting for actual DW consumption.

Probabilistic risk assessment - the keystone for the future of toxicology

Safety sciences must cope with uncertainty of models and results as well as information gaps. Acknowledging this uncer-tainty necessitates embracing probabilities and accepting the remaining risk. Every toxicological tool delivers only probable results. Traditionally, this is taken into account by using uncertainty / assessment factors and worst-case / precautionary approaches and thresholds. Probabilistic methods and Bayesian approaches seek to characterize these uncertainties and promise to support better risk assessment and, thereby, improve risk management decisions. Actual assessments of uncertainty can be more realistic than worst-case scenarios and may allow less conservative safety margins. Most importantly, as soon as we agree on uncertainty, this defines room for improvement and allows a transition from traditional to new approach methods as an engineering exercise. The objective nature of these mathematical tools allows to assign each methodology its fair place in evidence integration, whether in the context of risk assessment, sys-tematic reviews, or in the definition of an integrated testing strategy (ITS) / defined approach (DA) / integrated approach to testing and assessment (IATA). This article gives an overview of methods for probabilistic risk assessment and their application for exposure assessment, physiologically-based kinetic modelling, probability of hazard assessment (based on quantitative and read-across based structure-activity relationships, and mechanistic alerts from in vitro studies), indi-vidual susceptibility assessment, and evidence integration. Additional aspects are opportunities for uncertainty analysis of adverse outcome pathways and their relation to thresholds of toxicological concern. In conclusion, probabilistic risk assessment will be key for constructing a new toxicology paradigm - probably!

A consensus approach for estimating health risk: Application to inhalation cancer risks

Conducting a risk assessment is challenging because various and contrasting risk indicators are available, which can lead to discrepancies and, sometimes, conflicting conclusions. Constructing and using a consensus risk indicator (CRI) could provide a reliable alternative that is consistent and supports direct comparisons. The goal of this study is to propose a structured and pragmatic approach for constructing a CRI distribution and demonstrate its feasibility and easy implementation when conducting risk assessments. A CRI distribution is constructed as a weighted combination of existing indicators where the weights are obtained by using the overlapping areas of an individual indicator's distribution and an aggregated reference distribution. The approach is illustrated through an assessment of human cancer risk following inhalation exposure. The CRI is constructed using eight risk indicators. The CRI distribution parameters for 199 human carcinogenic chemicals associated with inhalation exposure were determined and are presented in an interactive table. To aid the wider implementation of the CRI approach, a user-friendly and interactive web application, named InCaRisk, was created to facilitate the cancer risk estimation following inhalation exposure. Our approach could be useful for enhancing the quality of regulatory decisions and protecting human health from environmental pollutants; our approach can be applied for a given health outcome, route of exposure and exposure setting.

Toxic effects and mechanisms of PFOA and its substitute GenX on the photosynthesis of Chlorella pyrenoidosa

Perfluorooctanoic acid (PFOA) and its substitute GenX are toxic chemicals that are widespread in the aquatic environment. However, there is little information about their toxicity mechanisms to aquatic organisms. In this study, Chlorella pyrenoidosa (C. pyrenoidosa) was treated with two concentrations (100 ng L^-1 and 100 μg L^-1) of PFOA or GenX for 12 days. The results showed that these two concentrations of PFOA and GenX began to inhibit the growth of algae after 6 days of treatment, and the Chlorophyll content and photosynthetic activity of C. pyrenoidosa were also negatively affected by these two chemicals. The transcriptomic results indicated that most of the genes related to the photosynthetic metabolism of C. pyrenoidosa were down-regulated (in 100 ng L^-1 treatment groups) on the 12th day. Besides, GenX and PFOA showed similar effects on algae photosynthesis including physical damage and metabolic disorders. According to this study, GenX might not be an ideal substitute for PFOA, and more attention should be paid on the management of emerging perfluoroalkyl substances.

Development of a quantitative chemical risk assessment (QCRA) procedure for contaminants of emerging concern in drinking water supply

The uncertainties on the occurrence, fate and hazard of Contaminants of Emerging Concern (CECs) increasingly challenge drinking water (DW) utilities whether additional measures should be taken to reduce the health risk. This has led to the development and evaluation of risk-based approaches by the scientific community. DW guideline values are commonly derived based on deterministic chemical risk assessment (CRA). Here, we propose a new probabilistic procedure, that is a quantitative chemical risk assessment (QCRA), to assess potential health risk related to the occurrence of CECs in DW. The QCRA includes uncertainties in risk calculation in both exposure and hazard assessments. To quantify the health risk in terms of the benchmark quotient probabilistic distribution, the QCRA estimates the probabilistic distribution of CECs concentration in DW based on their concentration in source water and simulating the breakthrough curves of a granular activated carbon (GAC) treatment process. The model inputs and output uncertainties were evaluated by sensitivity and uncertainty analyses for each step of the risk assessment to identify the most relevant factors affecting risk estimation. Dominant factors resulted to be the concentration of CECs in water sources, GAC isotherm parameters and toxicological data. To stress the potential of this new QCRA approach, several case studies are considered with focus on bisphenol A as an example CEC and various GAC management options. QCRA quantifies the probabilistic risk, providing more insight compared to CRA. QCRA proved to be more effective in supporting the intervention prioritization for treatment optimization to pursue health risk minimization.

Recent Advances in Probabilistic Dose-Response Assessment to Inform Risk-Based Decision Making

Paradoxically, risk assessments for the majority of chemicals lack any quantitative characterization as to the likelihood, incidence, or severity of the risks involved. The relatively few cases where "risk" is truly quantified are based on either epidemiologic data or extrapolation of experimental animal cancer bioassay data. The paucity of chemicals and health endpoints for which such data are available severely limits the ability of decisionmakers to account for the impacts of chemical exposures on human health. The development by the World Health Organization International Programme on Chemical Safety (WHO/IPCS) in 2014 of a comprehensive framework for probabilistic dose-response assessment has opened the door to a myriad of potential advances to better support decision making. Building on the pioneering work of Evans, Hattis, and Slob from the 1990s, the WHO/IPCS framework provides both a firm conceptual foundation as well as practical implementation tools to simultaneously assess uncertainty, variability, and severity of effect as a function of exposure. Moreover, such approaches do not depend on the availability of epidemiologic data, nor are they limited to cancer endpoints. Recent work has demonstrated the broad feasibility of such approaches in order to estimate the functional relationship between exposure level and the incidence or severity of health effects. While challenges remain, such as better characterization of the relationship between endpoints observed in experimental animal or in vitro studies and human health effects, the WHO/IPCS framework provides a strong basis for expanding the breadth of risk management decision contexts supported by chemical risk assessment.

Probabilistic approach for assessing cancer risk due to benzo[a]pyrene in barbecued meat: Informing advice for population groups

BACKGROUND

Consumption of meat prepared by barbecuing is associated with risk of cancer due to formation of carcinogenic compounds including benzo[a]pyrene (BaP). Assessment of a population's risk of disease and people's individual probability of disease given specific consumer attributes may direct food safety strategies to where impact on public health is largest. The aim of this study was to propose a model that estimates the risk of cancer caused by exposure to BaP from barbecued meat in Denmark, and to estimate the probability of developing cancer in subgroups of the population given different barbecuing frequencies.

METHODS

We developed probabilistic models applying two dimensional Monte Carlo simulation to take into account the variation in exposure given age and sex and in the individuals' sensitivity to develop cancer after exposure to BaP, and the uncertainty in the dose response model. We used the Danish dietary consumption survey, monitoring data of chemical concentrations, data on consumer behavior of frequency of barbecuing, and animal dose response data.

FINDINGS

We estimated an average extra lifetime risk of cancer due to BaP from barbecued meat of 6.8 × 10-5 (95% uncertainty interval 2.6 × 10-7 - 7.0 × 10-4) in the Danish population. This corresponds to approximately one to 4,074 extra cancer cases over a lifetime, reflecting wide uncertainty. The impact per barbecuing event on the risk of cancer for men and women of low body weight was higher compared to higher bodyweight. However, the difference due to sex and bodyweight between subgroups are dwarfed by the uncertainty.

INTERPRETATION

This study proposes a model that can be applied to other substances and routes of exposure, and allows for deriving the change in risk following a specific change in behaviour. The presented methodology can serve as a valuable tool for risk management, allowing for the formulation of behaviour advice targeted to specific sub-groups in the population.