A four-step approach to evaluate mixtures for consistency with dose addition

Hertzberg, Richard C.; Pan, Y.; Li, Ruosha; Haber, Lynne T.; Lyles, Robert H.; Herr, David W.; Moser, Virginia C.; Simmons, Jane Ellen

doi:10.1016/j.tox.2012.10.016

Cited by 23 publications

(15 citation statements)

References 39 publications

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“…Assessments of toxicity in binary [7], ternary [8] or complex chemical mixtures [9] have been common, with such toxicity having been evaluated for metals [10], pesticides [11], polycyclic aromatic hydrocarbons [12], [13], and micropollutants [14]. Conceptual studies and efforts to develop and evaluate mixture toxicity models [15], [16], [17], [18], [19], [20] have also provided approaches for improving toxicity assessment of mixtures.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of time-dependent toxicity and combined effects for a series of mono-halogenated acetonitrile-containing binary mixtures

2016

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Mixture and time-dependent toxicity (TDT) was assessed for a series of mono-halogenated acetonitrile-containing combinations. Inhibition of bioluminescence in Aliivibrio fischeri was measured after 15, 30 and 45-min of exposure. Concentration-response (x/y) curves were determined for each chemical alone at each timepoint, and used to develop predicted x/y curves for the dose-addition and independence models of combined effect. The x/y data for each binary mixture was then evaluated against the predicted mixture curves. Two metrics of mixture toxicity were calculated per combined effect model: (1) an EC50-based dose-addition (AQ) or independence (IQ) quotient and (2) the mixture/dose-addition (MX/DA) and mixture/independence (MX/I) metrics. For each single chemical and mixture tested, TDT was also calculated. After 45-min of exposure, 25 of 67 mixtures produced curves that were consistent with dose-addition using the MX/DA metric, with the other 42 being less toxic than predicted by MX/DA. Some mixtures had toxicity that was consistent with both dose-addition and independence. In general, those that were less toxic than predicted for dose-addition were also less toxic than predicted for independence. Of the 25 combinations that were consistent with dose-addition, 22 (88%) mixtures contained chemicals for which the individual TDT values were both >80%. In contrast, of the 42 non-dose-additive combinations, only 2 (4.8%) of the mixtures had both chemicals with individual TDT values >80%. The results support previous findings that TDT determinations can be useful for predicting chemical mixture toxicity.

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Section: Introductionmentioning

confidence: 99%

Evaluation of time-dependent toxicity and combined effects for a series of mono-halogenated acetonitrile-containing binary mixtures

2016

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“…Such research has included in vitro and in vivo studies (Boyd et al, 2013; Cedergreen et al, 2012; Coors et al, 2012), toxicity assessment using combined effects models (Crépet et al, 2013; Hertzberg et al, 2013; Moser et al, 2012; Rider et al, 2008; Webster, 2013), evaluating stressor impacts environmentally (Allan et al, 2012; Florian et al., 2013; Løkke 2010), risk assessment studies (Johnson et al, 2013; Løkke et al, 2013; Meek, 2013; Moore and Teed, 2013) and examining chemical reactivity within complex mixtures (Goel et al, 2013). Although the specifics of such research vary, the common goal is improving the ability to predict the effects of exposure to chemical mixtures.…”

Section: Introductionmentioning

confidence: 99%

Time-dependence in mixture toxicity prediction

Dawson

Allen

et al. 2014

Toxicology

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The value of time-dependent toxicity (TDT) data in predicting mixture toxicity was examined. Single chemical (A and B) and mixture (A + B) toxicity tests using Microtox® were conducted with inhibition of bioluminescence (Vibrio fischeri) being quantified after 15, 30 and 45-min of exposure. Single chemical and mixture tests for 25 sham (A1:A2) and 125 true (A:B) combinations had a minimum of seven duplicated concentrations with a duplicated control treatment for each test. Concentration/response (x/y) data were fitted to sigmoid curves using the five-parameter logistic minus one parameter (5PL-1P) function, from which slope, EC25, EC50, EC75, asymmetry, maximum effect, and r2 values were obtained for each chemical and mixture at each exposure duration. Toxicity data were used to calculate percentage-based TDT values for each individual chemical and mixture of each combination. Predicted TDT values for each mixture were calculated by averaging the TDT values of the individual components and regressed against the observed TDT values obtained in testing, resulting in strong correlations for both sham (r2 = 0.989, n = 25) and true mixtures (r2 = 0.944, n = 125). Additionally, regression analyses confirmed that observed mixture TDT values calculated for the 50% effect level were somewhat better correlated with predicted mixture TDT values than at the 25 and 75% effect levels. Single chemical and mixture TDT values were classified into five levels in order to discern trends. The results suggested that the ability to predict mixture TDT by averaging the TDT of the single agents was modestly reduced when one agent of the combination had a positive TDT value and the other had a minimal or negative TDT value.

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“…Previous (non-systematic) studies suggested that the adverse effects of mixtures of toxins were smaller than would be expected from addition of the individual effects caused by the single substances in mixtures (‘additive model’) (Hertzberg et al 2013 ). However, there are well-known exceptions: substances inducing enzymes, which metabolize and thereby activate chemicals, show stronger than additive effects in combination with their substrate chemicals; the same holds true for combinations of genotoxic carcinogens in combination with substances that inhibit DNA repair systems (Kortenkamp et al 2012 ; Ermler et al 2014 ).…”

Section: Current Scientific Topics In Toxicologymentioning

confidence: 99%

Toxicology: a discipline in need of academic anchoring—the point of view of the German Society of Toxicology

et al. 2015

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The paper describes the importance of toxicology as a discipline, its past achievements, current scientific challenges, and future development. Toxicological expertise is instrumental in the reduction of human health risks arising from chemicals and drugs. Toxicological assessment is needed to evaluate evidence and arguments, whether or not there is a scientific base for concern. The immense success already achieved by toxicological work is exemplified by reduced pollution of air, soil, water, and safer working places. Predominantly predictive toxicological testing is derived from the findings to assess risks to humans and the environment. Assessment of the adversity of molecular effects (including epigenetic effects), the effects of mixtures, and integration of exposure and biokinetics into in vitro testing are emerging challenges for toxicology. Toxicology is a translational science with its base in fundamental science. Academic institutions play an essential part by providing scientific innovation and education of young scientists.

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A four-step approach to evaluate mixtures for consistency with dose addition

Cited by 23 publications

References 39 publications

Evaluation of time-dependent toxicity and combined effects for a series of mono-halogenated acetonitrile-containing binary mixtures

Evaluation of time-dependent toxicity and combined effects for a series of mono-halogenated acetonitrile-containing binary mixtures

Time-dependence in mixture toxicity prediction

Toxicology: a discipline in need of academic anchoring—the point of view of the German Society of Toxicology

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