Scientific Basis for Expanding the Use of Interspecies Correlation Estimation Models

Bejarano, Adriana C.; Wheeler, James R.

doi:10.1002/ieam.4286

Cited by 8 publications

(11 citation statements)

References 5 publications

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“…One of the primary motivations of the present study was to further demonstrate the usefulness of ICE models. These models have clear amenable attributes for wider use, including regulatory applications (Bejarano and Wheeler 2020), and could prove useful in addressing the need for greater application of predictive models (OECD 2012; Hutchinson et al 2016). Therefore, ICE‐models have the potential to reduce the need to perform de nuevo vertebrate animal studies, helping to meet growing global legislative aspirations (see European Commission 2010; Burden et al 2015; Netherlands National Committee for the Protection of Animals Used for Scientific Purposes 2016; US Environmental Protection Agency 2018, 2019).…”

Section: Discussionmentioning

confidence: 99%

“…However, their incorporation for regulatory purposes requires acceptance by all stakeholders. As noted elsewhere (Bejarano and Wheeler 2020), broader acceptance of predictive models beyond QSARs could be achieved by creating a formal process for their incorporation into standard practice. Results from the present study and the future development of collaborative case studies could also enable greater acceptance of ICE models and increased confidence in their predictive ability.…”

Section: Discussionmentioning

confidence: 99%

“…The predictive ability of mathematical models relies on the quality of data used in their development. Data curation criteria were consistently applied to aquatic toxicity data in the present study, following guidance provided elsewhere (Raimondo et al 2007; Bejarano and Barron 2016; Bejarano and Wheeler 2020). Basic data attributes were as follows: 1) data on whole organisms reported as median lethal or effect concentrations (LC50 and EC50, respectively; mg/L); 2) studies clearly identifying the tested AE material, and the common/scientific name of the test species; and 3) studies documenting exposure conditions.…”

Section: Methodsmentioning

confidence: 99%

“…Despite calls at the international level for greater application of predictive models for regulating chemicals, and supporting chemical safety and hazard assessments (Organisation for Economic Co‐operation and Development [OECD] 2012; Hutchinson 2016), progress has been slow. Although ICE models were included in the fish toxicity testing framework of the OECD (2012) and have clear amenable attributes for their use in the regulatory context (Bejarano and Wheeler 2020), they have yet to be widely used for that purpose. A demonstration of practical applicability is one of the motivations of the present study.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Predictive Toxicity Models for Chemically Related Substances: A Case Study with Nonionic Alcohol Ethoxylate Surfactant

Bejarano

Wheeler

2021

Enviro Toxic and Chemistry

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Predictive toxicity models, including interspecies correlation estimation (ICE) models, are reliable alternatives to animal toxicity testing. The ICE models describe mathematical relationships facilitating toxicity prediction from one surrogate test species to a species of unknown sensitivity. The ICE models were developed from curated aquatic toxicity data for 19 nonionic alcohol ethoxylate (AE) surfactants manufactured through the same process. Comparison of AE-ICE predictions with observed values from external validation datasets indicates a reasonable predictive accuracy. Model predictions were also closer to observed values than predictions from previously published ICE models for other substance groups. Comparison of acute fifth percentile hazard concentrations (HC5s) from species sensitivity distributions enhanced with AE-ICE predictions with chronic HC5s published elsewhere produced an acute-to-chronic ratio of 5, which was used to estimate chronic HC5s. With both acute and chronic HC5s for 14 AE substances, regressions were made relative to their respective liposome-water partitioning coefficients (log K lipw ), resulting in HC5-log K lipw relationships useful in estimating HC5s for AE substances with known composition but with limited or unavailable toxicity data. The findings from this case study further demonstrate that ICE models are viable alternatives to toxicity testing and could be used as weight of evidence in hazard assessment evaluations.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Predictive Toxicity Models for Chemically Related Substances: A Case Study with Nonionic Alcohol Ethoxylate Surfactant

Bejarano

Wheeler

2021

Enviro Toxic and Chemistry

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“…Interspecies correlation estimation (ICE) models predict toxicity to a species with limited data using a known toxicity value in a surrogate species [ 1 ]. The need to evaluate a rapidly growing number of chemicals and efforts to reduce or replace animal testing have increased the need and use of computational toxicity estimation methods, such as ICE models [ 2 ]. Most ICE models have been developed as simple linear regressions of acute toxicity values of the same chemicals tested in both the surrogate and predicted species [ 3 ].…”

Section: Introductionmentioning

confidence: 99%

Potential for Interspecies Toxicity Estimation in Soil Invertebrates

Barron

Lambert

2021

Toxics

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Interspecies correlation estimation (ICE) models are linear regressions that predict toxicity to a species with few data using a known toxicity value in a surrogate species. ICE models are well established for estimating toxicity to fish and aquatic invertebrates but have not been generally developed or applied to soil organisms. To facilitate the development of ICE models for soil invertebrates, a database of single chemical toxicity values was compiled from knowledgebases and reports that included 853 records encompassing 192 chemicals and 12 species. Most toxicity data for single chemicals tested in soil media were for species of earthworms, with only limited data for other species and taxa. ICE models were developed for eleven separate species pairs as least squares log-linear regressions of acute toxicity values of the same chemicals tested in both the surrogate and predicted species of soil organisms. Model uncertainty was assessed using leave one out cross-validation as the fold difference between a predicted and measured toxicity value. ICE models showed high accuracy within order (e.g., earthworm to earthworm), but less prediction accuracy in the two across-taxa models (Arthropoda to Annelida and the inverse). This study provides a proof-of-concept demonstration that ICE models can be developed for soil invertebrates.

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A Critical Review of the Availability, Reliability, and Ecological Relevance of Arctic Species Toxicity Tests for Use in Environmental Risk Assessment

Eldridge

Jourdan

Hanson

2021

Enviro Toxic and Chemistry

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There is a pressing need to understand the impact of contaminants on Arctic ecosystems; however, most toxicity tests are based on temperate species, and there are issues with reliability and relevance of bioassays in general. Together this may result in an underestimation of harm to Arctic organisms and contribute to significant uncertainty in risk assessments. To help address these concerns, a critical review to assess reported effects for these species, quantify methodological and endpoint relevance gaps, and identify future research needs for testing was performed. We developed uniform criteria to score each study, allowing an objective comparison across experiments to quantify their reliability and relevance. We scored a total of 48 individual studies, capturing 39 tested compounds, 73 unique Arctic test species, and 95 distinct endpoints published from 1975 to 2021. Our analysis shows that of 253 test substance and species combinations scored (i.e., a unique toxicity test), 207 (82%) failed to meet at least one critical study criterion that contributes to data reliability for use in risk assessment. Arctic-focused toxicity testing needs to ensure that exposures can be analytically confirmed, include environmentally realistic exposure scenarios, and report test methods more thoroughly. Significant data gaps were identified as related to standardized toxicity testing with Arctic species, diversity of compounds tested with these organisms, and the inclusion of ecologically relevant sublethal and chronic endpoints assessed in Arctic toxicity testing. Overall, there needs to be ongoing improvement in test conduction and reporting in the scientific literature to support effective risk assessments in an Arctic context.

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Scientific Basis for Expanding the Use of Interspecies Correlation Estimation Models

Cited by 8 publications

References 5 publications

Predictive Toxicity Models for Chemically Related Substances: A Case Study with Nonionic Alcohol Ethoxylate Surfactant

Predictive Toxicity Models for Chemically Related Substances: A Case Study with Nonionic Alcohol Ethoxylate Surfactant

Potential for Interspecies Toxicity Estimation in Soil Invertebrates

A Critical Review of the Availability, Reliability, and Ecological Relevance of Arctic Species Toxicity Tests for Use in Environmental Risk Assessment

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