Dose-Related Severity Sequence, and Risk-Based Integration, of Chemically Induced Health Effects

Guidance on risk-benefit assessment of foods

The EFSA Scientific Committee has updated its 2010 Guidance on risk-benefit assessment (RBA) of foods. The update addresses methodological developments and regulatory needs. While it retains the stepwise RBA approach, it provides additional methods for complex assessments, such as multiple chemical hazards and all relevant health effects impacting different population subgroups. The updated guidance includes approaches for systematic identification, prioritisation and selection of hazardous and beneficial food components. It also offers updates relevant to characterising adverse and beneficial effects, such as measures of effect size and dose-response modelling. The guidance expands options for characterising risks and benefits, incorporating variability, uncertainty, severity categorisation and ranking of different (beneficial or adverse) effects. The impact of different types of health effects is assessed qualitatively or quantitatively, depending on the problem formulation, scope of the RBA question and data availability. The integration of risks and benefits often involves value-based judgements and should ideally be performed with the risk-benefit manager. Metrics such as Disability-Adjusted Life Years (DALYs) and Quality-Adjusted Life Years (QALYs) can be used. Additional approaches are presented, such as probability of all relevant effects and/or effects of given severities and their integration using severity weight functions. The update includes practical guidance on reporting results, interpreting outcomes and communicating the outcome of an RBA, considering consumer perspectives and responses to advice.

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 common approach for ranking of microbiological and chemical hazards in foods based on risk assessment - useful but is it possible?

This article compares and contrasts microbial and chemical risk assessment methodologies in order to evaluate the potential for a common framework for ranking of risk of chemical and microbiological hazards, and developments needed for such a framework. An overview of microbial (MRA) and chemical (CRA) risk assessment is presented and important differences are highlighted. Two microbiological and two chemical hazard-food combinations were ranked based on both a margin of exposure and a risk assessment approach. The comparisons illustrated that it is possible to rank chemical and microbiological hazard-food combinations with traditional approaches from each domain and indicated that the rank order but not the absolute measures is similar using either approach. Including severity in the assessment using DALY reduced differences between hazards and affected the outcome more than which approach was used. Ranking frameworks should include assessment of uncertainty as an integral part of the ranking, and be based on assessment of risk, not safety, and expressed in a common health metric such as disease burden. Necessary simplifications to address data gaps can involve the use of default scenarios. Challenges include comparisons of case-based vs. non-case-based health-endpoints, e.g. biomarker concentration, and integration of the severity of health effects into ranking.