The NAS Perchlorate Review: Questions Remain about the Perchlorate RfD

Human exposure to perchlorate is commonplace because it is a contaminant of drinking water, certain foods, and breast milk. The U.S. Environmental Protection Agency (EPA) conducted a perchlorate risk assessment in 2002 that yielded a reference dose (RfD) based on both the animal and human toxicology data. This assessment has been superceded by a recent National Academy of Science (NAS) review that derived a perchlorate RfD that is 20-fold greater (less stringent) than that derived by the U.S. EPA in 2002. The NAS-derived RfD was put on the U.S. EPA’s Integrated Risk Information System (IRIS) database very quickly and with no further public review. In this commentary we raise concerns about the NAS approach to RfD development in three areas of toxicity assessment: the dose that the NAS described as a no observable adverse-effect level is actually associated with perchlorate-induced effects; consideration of uncertainties was insufficient; and the NAS considered the inhibition of iodine uptake to be a nonadverse effect. We conclude that risk assessors should carefully evaluate whether the IRIS RfD is the most appropriate value for assessing perchlorate risk

Safety assessment of the substance phosphorous acid, mixed 2,4-bis(1,1-dimethylpropyl)phenyl and 4-(1,1-dimethylpropyl)phenyl triesters for use in food contact materials

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Risks to human and animal health related to the presence of deoxynivalenol and its acetylated and modified forms in food and feed

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Scientific Opinion on Flavouring Group Evaluation 57, Revision 1 (FGE.57Rev1): consideration of isopulegone and three flavouring substances evaluated by JECFA (55th meeting)

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Scientific Opinion on Flavouring Group Evaluation 302 (FGE.302): N-(2-methylcyclohexyl)-2,3,4,5,6-pentafluoro-benzamide from Chemical Group 30

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Cumulative Exposure Assessment of Triazole Pesticides

In the EFSA opinion on identification of new approaches to assess cumulative and synergistic risks from pesticides to human health a tiered approach for cumulative risk assessment has been proposed. The first tier is a deterministic approach using average and large portion consumption statistics. The higher tiers include probabilistic exposure assessment and Benchmark Dose (BMD) modeling. The aim of this study is to demonstrate the feasibility and applicability of a higher tier assessment of cumulative exposure using probabilistic modeling in combination with the relative potency factor (RPF) approach. The RPFs are used to weigh the toxicity of each pesticide relative to the toxicity of a chosen index compound (pesticide). In this report the authors address both the short-term and long-term cumulative exposure to triazoles using different statistical model

A Case for Caution: An Evaluation of Calabrese and Baldwin\u27s Studies of Chemical Hormesis

Suggesting a need for more research, Mr. Elliott argues that it is too soon for risk-assessment policy to account for recent challenges to a toxicological linear dose-response assumption

Why De Minimis?

De minimis cutoffs are a familiar feature of risk regulation. This includes the quantitative individual risk thresholds for fatality risks employed in many contexts by EPA, FDA, and other agencies, such as the 1-in-1 million lifetime cancer risk cutoff; extreme event cutoffs for addressing natural hazards, such as the 100 - year - flood or 475 - year - earthquake; de minimis failure probabilities for built structures; the exclusion of low - probability causal models; and other policymaking criteria. All these tests have a common structure, as I show in the Article. A de minimis test, broadly defined, tells the decisionmaker to determine whether the probability of some outcome is above a low threshold and makes this determination relevant, in some way, to her choice. De minimis cutoffs are deeply problematic, and have been generally misunderstood by scholars. First, they are warranted - if at all - by virtue of policymakers\u27 bounded rationality. If policymakers were fully rational, de minimis cutoffs would have no justification. (This is true, I suggest, across a wide range of normative theories, and for the full gamut of de minimis tests). Second, although it seems plausible that some de minimis tests are justified once bounded rationality is brought into the picture, it is not clear which those are, or even how we should go about identifying them