From: "Stuart, Ralph" <Ralph.Stuart**At_Symbol_Here**keene.edu>
Subject: [DCHAS-L] Assessing potential risks from exposure to chemical mixtures – JRC review of case studies
Date: Sat, 9 Jul 2016 13:36:43 +0000
Reply-To: DCHAS-L <DCHAS-L**At_Symbol_Here**MED.CORNELL.EDU>
Message-ID: 216DB0B7-9C84-4DB1-8E57-2BE459FB1084**At_Symbol_Here**keene.edu


https://urldefense.proofpoint.com/v2/url?u=https-3A__eurl-2Decvam.jrc.ec.europa.eu_assessing-2Dpotential-2Drisks-2Dfrom-2Dexposure-2Dto-2Dchemical-2Dmixtures-2D2013-2Djrc-2Dreview-2Dof-2Dcase-2Dstudies&d=DQIGaQ&c=lb62iw4YL4RFalcE2hQUQealT9-RXrryqt9KZX2qu2s&r=meWM1Buqv4IQ27AlK1OJRjcQl09S1Zta6YXKalY_Io0&m=ymMdFOIn1772w4K41R2vg_-VdimaVR-zXy5umqWGRJU&s=nVrHMs21VXK5vCs-0wi5rtOzoCNlwZ5jDeoWvVn8kK4&e=

A review of case studies assessing the risk from exposure to chemical mixtures shows a potential concern for several groups of chemicals for highly exposed or particularly vulnerable population groups.

Humans and wildlife can be exposed to an almost infinite number of different combinations of chemicals in mixtures via food, consumer products and the environment, which raises concerns for possible impacts on public and environmental health. A review of recent literature by the JRC's EU Reference Laboratory for Alternatives to Animal Testing (EURL ECVAM) summarises the outcome of case studies covering several chemical classes. Parameters that could lead to an over- or underestimation of potential risks were identified. Case study results need to be interpreted with caution, considering the underlying assumptions, model parameters and related uncertainties. However, there is clear evidence that chemicals need to be further addressed not only in single substance risk assessments but also in mixture assessments that cover multiple chemical classes and legislative sectors.

Furthermore, several issues hampering mixture risk assessments are identified. In order to perform a mixture risk assessment, the composition of the mixture in terms of chemical components and their concentrations need to be known, and information on their uptake and toxicity are required. Screening level assessments based on conservative assumptions are generally possible. However, refining such assessments to more realistic exposure scenarios is often not feasible due to data gaps. In particular, relevant exposure and toxicity data as well as information on modes of action are often lacking.

Future case studies on mixture risk assessment could fill the knowledge gaps identified in this review. Such case studies could help by addressing differences between population groups, investigating different and emerging groups of substances, considering the relevance of interactions (i.e. synergisms), examining different approaches for the grouping of chemicals, and especially by investigating mixtures of potential concern that cross regulatory sectors.

Background

The risk assessment of chemicals for regulatory purposes does not generally take into account the Č??real lifeČ?? exposure to multiple substances, but mainly relies on the assessment of individual substances. A JRC report on regulatory requirements for the assessment of mixtures published in 2014 shows that combined exposures are considered in several pieces of legislation, however a harmonised consistent approach on performing mixture assessments across different regulatory sectors is still lacking.

It is practically impossible to test all possible chemical mixtures experimentally. Therefore smart strategies are needed to assess the potential hazards using new tools that rely less on in vivo testing and incorporate instead alternative experimental and computational tools. Novel, non-animal tools and scientific methodologies show high potential for the assessment of combined effects of chemicals on humans and the environment. They allow meaningful information on individual mixture components or whole mixtures to be derived, enabling a better understanding of the underlying mechanisms of their effects (see report by JRC's EU Reference Laboratory for Alternatives to Animal Testing (EURL ECVAM)).


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