A value of information framework for assessing the trade-offs associated with uncertainty, duration, and cost of chemical toxicity testing.

A number of investigators have explored the use of value of information (VOI) analysis to evaluate alternative information collection procedures in diverse decision-making contexts. This paper presents an analytic framework for determining the value of toxicity information used in risk-based decision making. The framework is specifically designed to explore the trade-offs between cost, timeliness, and uncertainty reduction associated with different toxicity-testing methodologies. The use of the proposed framework is demonstrated by two illustrative applications which, although based on simplified assumptions, show the insights that can be obtained through the use of VOI analysis. Specifically, these results suggest that timeliness of information collection has a significant impact on estimates of the VOI of chemical toxicity tests, even in the presence of smaller reductions in uncertainty. The framework introduces the concept of the expected value of delayed sample information, as an extension to the usual expected value of sample information, to accommodate the reductions in value resulting from delayed decision making. Our analysis also suggests that lower cost and higher throughput testing also may be beneficial in terms of public health benefits by increasing the number of substances that can be evaluated within a given budget. When the relative value is expressed in terms of return-on-investment per testing strategy, the differences can be substantial.

Development of an Evidence-Based Risk Assessment Framework.

Assessment of potential human health risks associated with environmental and other agents requires careful evaluation of all available and relevant evidence for the agent of interest, including both data-rich and data-poor agents. With the advent of new approach methodologies in toxicological risk assessment, guidance on integrating evidence from mul-tiple evidence streams is needed to ensure that all available data is given due consideration in both qualitative and quantitative risk assessment. The present report summarizes the discussions among academic, government, and private sector participants from North America and Europe in an international workshop convened to explore the development of an evidence-based risk assessment framework, taking into account all available evidence in an appropriate manner in order to arrive at the best possible characterization of potential human health risks and associated uncertainty. Although consensus among workshop participants was not a specific goal, there was general agreement on the key consider-ations involved in evidence-based risk assessment incorporating 21st century science into human health risk assessment. These considerations have been embodied into an overarching prototype framework for evidence integration that will be explored in more depth in a follow-up meeting.

A Framework that Considers the Impacts of Time, Cost, and Uncertainty in the Determination of the Cost Effectiveness of Toxicity-Testing Methodologies.

Regulatory agencies are required to evaluate the impacts of thousands of chemicals. Toxicological tests currently used in such evaluations are time-consuming and resource intensive; however, advances in toxicology and related fields are providing new testing methodologies that reduce the cost and time required for testing. The selection of a preferred methodology is challenging because the new methodologies vary in duration and cost, and the data they generate vary in the level of uncertainty. This article presents a framework for performing cost-effectiveness analyses (CEAs) of toxicity tests that account for cost, duration, and uncertainty. This is achieved by using an output metric-the cost per correct regulatory decision-that reflects the three elements. The framework is demonstrated in two example CEAs, one for a simple decision of risk acceptability and a second, more complex decision, involving the selection of regulatory actions. Each example CEA evaluates five hypothetical toxicity-testing methodologies which differ with respect to cost, time, and uncertainty. The results of the examples indicate that either a fivefold reduction in cost or duration can be a larger driver of the selection of an optimal toxicity-testing methodology than a fivefold reduction in uncertainty. Uncertainty becomes of similar importance to cost and duration when decisionmakers are required to make more complex decisions that require the determination of small differences in risk predictions. The framework presented in this article may provide a useful basis for the identification of cost-effective methods for toxicity testing of large numbers of chemicals.

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.

Advancements in Life Cycle Human Exposure and Toxicity Characterization.

BACKGROUND: The Life Cycle Initiative, hosted at the United Nations Environment Programme, selected human toxicity impacts from exposure to chemical substances as an impact category that requires global guidance to overcome current assessment challenges. The initiative leadership established the Human Toxicity Task Force to develop guidance on assessing human exposure and toxicity impacts. Based on input gathered at three workshops addressing the main current scientific challenges and questions, the task force built a roadmap for advancing human toxicity characterization, primarily for use in life cycle impact assessment (LCIA). OBJECTIVES: The present paper aims at reporting on the outcomes of the task force workshops along with interpretation of how these outcomes will impact the practice and reliability of toxicity characterization. The task force thereby focuses on two major issues that emerged from the workshops, namely considering near-field exposures and improving dose­response modeling. DISCUSSION: The task force recommended approaches to improve the assessment of human exposure, including capturing missing exposure settings and human receptor pathways by coupling additional fate and exposure processes in consumer and occupational environments (near field) with existing processes in outdoor environments (far field). To quantify overall aggregate exposure, the task force suggested that environments be coupled using a consistent set of quantified chemical mass fractions transferred among environmental compartments. With respect to dose­response, the task force was concerned about the way LCIA currently characterizes human toxicity effects, and discussed several potential solutions. A specific concern is the use of a (linear) dose­response extrapolation to zero. Another concern addresses the challenge of identifying a metric for human toxicity impacts that is aligned with the spatiotemporal resolution of present LCIA methodology, yet is adequate to indicate health impact potential. CONCLUSIONS: Further research efforts are required based on our proposed set of recommendations for improving the characterization of human exposure and toxicity impacts in LCIA and other comparative assessment frameworks. https://doi.org/10.1289/EHP3871.

Beyond the RfD: Broad Application of a Probabilistic Approach to Improve Chemical Dose-Response Assessments for Noncancer Effects.

BACKGROUND: The National Academies recommended risk assessments redefine the traditional noncancer Reference Dose (RfD) as a probabilistically derived risk-specific dose, a framework for which was recently developed by the World Health Organization (WHO). OBJECTIVES: Our aim was to assess the feasibility and implications of replacing traditional RfDs with probabilistic estimates of the human dose associated with an effect magnitude M and population incidence I (HDMI). METHODS: We created a comprehensive, curated database of RfDs derived from animal data and developed a standardized, automated, web-accessible probabilistic dose-response workflow implementing the WHO framework. RESULTS: We identified 1,464 RfDs and associated endpoints, representing 608 chemicals across many types of effects. Applying our standardized workflow resulted in 1,522 HDMI values. Traditional RfDs are generally within an order of magnitude of the HDMI lower confidence bound for I=1% and M values commonly used for benchmark doses. The greatest contributor to uncertainty was lack of benchmark dose estimates, followed by uncertainty in the extent of human variability. Exposure at the traditional RfD frequently implies an upper 95% confidence bound of several percent of the population affected. Whether such incidences are considered acceptable is likely to vary by chemical and risk context, especially given the wide range of severity of the associated effects, from clinical chemistry to mortality. CONCLUSIONS: Overall, replacing RfDs with HDMI estimates can provide a more consistent, scientifically rigorous, and transparent basis for risk management decisions, as well as support additional decision contexts such as economic benefit-cost analysis, risk-risk tradeoffs, life-cycle impact analysis, and emergency response. https://doi.org/10.1289/EHP3368.

Determining the applicability of threshold of toxicological concern approaches to substances found in foods.

Threshold of Toxicological Concern (TTC) decision-support methods present a pragmatic approach to using data from well-characterized chemicals and protective estimates of exposure in a stepwise fashion to inform decisions regarding low-level exposures to chemicals for which few data exist. It is based on structural and functional categorizations of chemicals derived from decades of animal testing with a wide variety of chemicals. Expertise is required to use the TTC methods, and there are situations in which its use is clearly inappropriate or not currently supported. To facilitate proper use of the TTC, this paper describes issues to be considered by risk managers when faced with the situation of an unexpected substance in food. Case studies are provided to illustrate the implementation of these considerations, demonstrating the steps taken in deciding whether it would be appropriate to apply the TTC approach in each case. By appropriately applying the methods, employing the appropriate scientific expertise, and combining use with the conservative assumptions embedded within the derivation of the thresholds, the TTC can realize its potential to protect public health and to contribute to efficient use of resources in food safety risk management.

A survey of frameworks for best practices in weight-of-evidence analyses.

The National Academy of Sciences (NAS) Review of the Environmental Protection Agency's Draft IRIS Assessment of Formaldehyde proposed a "roadmap" for reform and improvement of the Agency's risk assessment process. Specifically, it called for development of a transparent and defensible methodology for weight-of-evidence (WoE) assessments. To facilitate development of an improved process, we developed a white paper that reviewed approximately 50 existing WoE frameworks, seeking insights from their variations and nominating best practices for WoE analyses of causation of chemical risks. Four phases of WoE analysis were identified and evaluated in each framework: (1) defining the causal question and developing criteria for study selection, (2) developing and applying criteria for review of individual studies, (3) evaluating and integrating evidence and (4) drawing conclusions based on inferences. We circulated the draft white paper to stakeholders and then held a facilitated, multi-disciplinary invited stakeholder workshop to broaden and deepen the discussion on methods, rationales, utility and limitations among the surveyed WoE frameworks. The workshop developed recommendations for improving the conduct of WoE evaluations. Based on the analysis of the 50 frameworks and discussions at the workshop, best practices in conducting WoE analyses were identified for each of the four phases. Many of these best practices noted from the analysis and workshop could be implemented immediately, while others may require additional refinement as part of the ongoing discussions for improving the scientific basis of chemical risk assessments.

Drinking water as a proportion of total human exposure to volatile N-nitrosamines.

Some volatile N-nitrosamines, primarily N-nitrosodimethylamine (NDMA), are recognized as products of drinking water treatment at ng/L levels and as known carcinogens. The U.S. EPA has identified the N-nitrosamines as contaminants being considered for regulation as a group under the Safe Drinking Water Act. Nitrosamines are common dietary components, and a major database (over 18,000 drinking water samples) has recently been created under the Unregulated Contaminant Monitoring Rule. A Monte Carlo modeling analysis in 2007 found that drinking water contributed less than 2.8% of ingested NDMA and less than 0.02% of total NDMA exposure when estimated endogenous formation was considered. Our analysis, based upon human blood concentrations, indicates that endogenous NDMA production is larger than expected. The blood-based estimates are within the range that would be calculated from estimates based on daily urinary NDMA excretion and an estimate based on methylated guanine in DNA of lymphocytes from human volunteers. Our analysis of ingested NDMA from food and water based on Monte Carlo modeling with more complete data input shows that drinking water contributes a mean proportion of the lifetime average daily NDMA dose ranging from between 0.0002% and 0.001% for surface water systems using free chlorine or between 0.001% and 0.01% for surface water systems using chloramines. The proportions of average daily dose are higher for infants (zero to six months) than other age cohorts, with the highest mean up to 0.09% (upper 95th percentile of 0.3%).

FDA-iRISK--a comparative risk assessment system for evaluating and ranking food-hazard pairs: case studies on microbial hazards.

Stakeholders in the system of food safety, in particular federal agencies, need evidence-based, transparent, and rigorous approaches to estimate and compare the risk of foodborne illness from microbial and chemical hazards and the public health impact of interventions. FDA-iRISK (referred to here as iRISK), a Web-based quantitative risk assessment system, was developed to meet this need. The modeling tool enables users to assess, compare, and rank the risks posed by multiple food-hazard pairs at all stages of the food supply system, from primary production, through manufacturing and processing, to retail distribution and, ultimately, to the consumer. Using standard data entry templates, built-in mathematical functions, and Monte Carlo simulation techniques, iRISK integrates data and assumptions from seven components: the food, the hazard, the population of consumers, process models describing the introduction and fate of the hazard up to the point of consumption, consumption patterns, dose-response curves, and health effects. Beyond risk ranking, iRISK enables users to estimate and compare the impact of interventions and control measures on public health risk. iRISK provides estimates of the impact of proposed interventions in various ways, including changes in the mean risk of illness and burden of disease metrics, such as losses in disability-adjusted life years. Case studies for Listeria monocytogenes and Salmonella were developed to demonstrate the application of iRISK for the estimation of risks and the impact of interventions for microbial hazards. iRISK was made available to the public at http://irisk.foodrisk.org in October 2012.

Nano risk analysis: advancing the science for nanomaterials risk management.

Scientists, activists, industry, and governments have raised concerns about health and environmental risks of nanoscale materials. The Society for Risk Analysis convened experts in September 2008 in Washington, DC to deliberate on issues relating to the unique attributes of nanoscale materials that raise novel concerns about health risks. This article reports on the overall themes and findings of the workshop, uncovering the underlying issues for each of these topics that become recurring themes. The attributes of nanoscale particles and other nanomaterials that present novel issues for risk analysis are evaluated in a risk analysis framework, identifying challenges and opportunities for risk analysts and others seeking to assess and manage the risks from emerging nanoscale materials and nanotechnologies. Workshop deliberations and recommendations for advancing the risk analysis and management of nanotechnologies are presented.

Quantitative risk assessment of Listeria monocytogenes in ready-to-eat meats in Australia.

Listeria monocytogenes is a food-borne pathogen that can contaminate processed meats and has caused outbreaks in several nations in which processed meats were the vehicle. Due to its ecology, the control of this organism in ready-to-eat meats is difficult. As a first step in improving risk management for this product:pathogen pair in Australia, a stochastic simulation model to predict the numbers of L. monocytogenes likely to be consumed in those products under a wide range of scenarios was developed. The predictions are based on data describing initial contamination levels of both lactic acid bacteria and L. monocytogenes, product formulation, times and temperatures of distribution and storage prior to consumption, and consumption patterns. The model was used to estimate the probable numbers of cases of listeriosis due to processed meats in Australia per year. The model predicted that processed meats could be responsible for up to approximately 40% of cases of listeriosis in Australia, a level considered credible by comparison with available epidemiological data. The reliability of the model, as well as data gaps and further research needs, is discussed.

Models of the behavior of Escherichia coli O157:H7 in raw sterile ground beef stored at 5 to 46 degrees C.

Escherichia coli O157:H7 can contaminate raw ground beef and cause serious human foodborne illness. Previous reports describe the behavior of E. coli O157:H7 in ground beef under different storage conditions; however, models are lacking for the pathogen's behavior in raw ground beef stored over a broad range of temperature. Using sterile irradiated raw ground beef, the behavioral kinetics of 10 individual E. coli O157:H7 strains and/or a 5- or 10-strain cocktail were measured at storage temperatures from 5 degrees to 46 degrees C. Growth occurred from 6 to 45 degrees C. Although lag phase duration (LPD) decreased from 10.5 to 45 degrees C, no lag phase was observed at 6, 8, or 10 degrees C. The specific growth rate (SGR) increased from 6 to 42 degrees C then declined up to 45 degrees C. In contrast to these profiles, the maximum population density (MPD) declined with increasing temperature, from approximately 9.7 to 8.2 log cfu/g. Bias (B(f)) and accuracy (A(f)) factors for an E. coli O157:H7 broth-based aerobic growth model (10 to 42 degrees C) applied to the observations in ground beef were 1.05, 2.70, 1.00 and 1.29, 2.87, 1.03, for SGR, LPD and MPD, respectively. New secondary models increased the accuracy of predictions (5 to 45 degrees C), with B(f) and A(f) for SGR, LPD, and MPD of 1.00, 1.06, and 1.00 and 1.14, 1.33, and 1.02, respectively. These new models offer improved tools for designing and implementing food safety systems and assessing the impact of E. coli O157:H7 disease.

A probabilistic analysis of Clostridium perfringens growth during food service operations.

The purpose of this study was threefold: first, the study was designed to illustrate the use of data and information collected in food safety surveys in a quantitative risk assessment. In this case, the focus was on the food service industry; however, similar data from other parts of the food chain could be similarly incorporated. The second objective was to quantitatively describe and better understand the role that the food service industry plays in the safety of food. The third objective was to illustrate the additional decision-making information that is available when uncertainty and variability are incorporated into the modelling of systems.