Severity of effect considerations regarding the use of mutation as a toxicological endpoint for risk assessment: A report from the 8th International Workshop on Genotoxicity Testing (IWGT).

Exposure levels without appreciable human health risk may be determined by dividing a point of departure on a dose-response curve (e.g., benchmark dose) by a composite adjustment factor (AF). An "effect severity" AF (ESAF) is employed in some regulatory contexts. An ESAF of 10 may be incorporated in the derivation of a health-based guidance value (HBGV) when a "severe" toxicological endpoint, such as teratogenicity, irreversible reproductive effects, neurotoxicity, or cancer was observed in the reference study. Although mutation data have been used historically for hazard identification, this endpoint is suitable for quantitative dose-response modeling and risk assessment. As part of the 8th International Workshops on Genotoxicity Testing, a sub-group of the Quantitative Analysis Work Group (WG) explored how the concept of effect severity could be applied to mutation. To approach this question, the WG reviewed the prevailing regulatory guidance on how an ESAF is incorporated into risk assessments, evaluated current knowledge of associations between germline or somatic mutation and severe disease risk, and mined available data on the fraction of human germline mutations expected to cause severe disease. Based on this review and given that mutations are irreversible and some cause severe human disease, in regulatory settings where an ESAF is used, a majority of the WG recommends applying an ESAF value between 2 and 10 when deriving a HBGV from mutation data. This recommendation may need to be revisited in the future if direct measurement of disease-causing mutations by error-corrected next generation sequencing clarifies selection of ESAF values.

Interpretation of in vitro concentration-response data for risk assessment and regulatory decision-making: Report from the 2022 IWGT quantitative analysis expert working group meeting.

Quantitative risk assessments of chemicals are routinely performed using in vivo data from rodents; however, there is growing recognition that non-animal approaches can be human-relevant alternatives. There is an urgent need to build confidence in non-animal alternatives given the international support to reduce the use of animals in toxicity testing where possible. In order for scientists and risk assessors to prepare for this paradigm shift in toxicity assessment, standardization and consensus on in vitro testing strategies and data interpretation will need to be established. To address this issue, an Expert Working Group (EWG) of the 8th International Workshop on Genotoxicity Testing (IWGT) evaluated the utility of quantitative in vitro genotoxicity concentration-response data for risk assessment. The EWG first evaluated available in vitro methodologies and then examined the variability and maximal response of in vitro tests to estimate biologically relevant values for the critical effect sizes considered adverse or unacceptable. Next, the EWG reviewed the approaches and computational models employed to provide human-relevant dose context to in vitro data. Lastly, the EWG evaluated risk assessment applications for which in vitro data are ready for use and applications where further work is required. The EWG concluded that in vitro genotoxicity concentration-response data can be interpreted in a risk assessment context. However, prior to routine use in regulatory settings, further research will be required to address the remaining uncertainties and limitations.

Application of a new approach methodology (NAM)-based strategy for genotoxicity assessment of data-poor compounds.

The conventional battery for genotoxicity testing is not well suited to assessing the large number of chemicals needing evaluation. Traditional in vitro tests lack throughput, provide little mechanistic information, and have poor specificity in predicting in vivo genotoxicity. New Approach Methodologies (NAMs) aim to accelerate the pace of hazard assessment and reduce reliance on in vivo tests that are time-consuming and resource-intensive. As such, high-throughput transcriptomic and flow cytometry-based assays have been developed for modernized in vitro genotoxicity assessment. This includes: the TGx-DDI transcriptomic biomarker (i.e., 64-gene expression signature to identify DNA damage-inducing (DDI) substances), the MicroFlow® assay (i.e., a flow cytometry-based micronucleus (MN) test), and the MultiFlow® assay (i.e., a multiplexed flow cytometry-based reporter assay that yields mode of action (MoA) information). The objective of this study was to investigate the utility of the TGx-DDI transcriptomic biomarker, multiplexed with the MicroFlow® and MultiFlow® assays, as an integrated NAM-based testing strategy for screening data-poor compounds prioritized by Health Canada's New Substances Assessment and Control Bureau. Human lymphoblastoid TK6 cells were exposed to 3 control and 10 data-poor substances, using a 6-point concentration range. Gene expression profiling was conducted using the targeted TempO-Seq™ assay, and the TGx-DDI classifier was applied to the dataset. Classifications were compared with those based on the MicroFlow® and MultiFlow® assays. Benchmark Concentration (BMC) modeling was used for potency ranking. The results of the integrated hazard calls indicate that five of the data-poor compounds were genotoxic in vitro, causing DNA damage via a clastogenic MoA, and one via a pan-genotoxic MoA. Two compounds were likely irrelevant positives in the MN test; two are considered possibly genotoxic causing DNA damage via an ambiguous MoA. BMC modeling revealed nearly identical potency rankings for each assay. This ranking was maintained when all endpoint BMCs were converted into a single score using the Toxicological Prioritization (ToxPi) approach. Overall, this study contributes to the establishment of a modernized approach for effective genotoxicity assessment and chemical prioritization for further regulatory scrutiny. We conclude that the integration of TGx-DDI, MicroFlow®, and MultiFlow® endpoints is an effective NAM-based strategy for genotoxicity assessment of data-poor compounds.

Quantitative Interpretation of Genetic Toxicity Dose-Response Data for Risk Assessment and Regulatory Decision-Making: Current Status and Emerging Priorities.

The screen-and-bin approach for interpretation of genotoxicity data is predicated on three false assumptions: that genotoxicants are rare, that genotoxicity dose-response functions do not contain a low-dose region mechanistically characterized by zero-order kinetics, and that genotoxicity is not a bona fide toxicological endpoint. Consequently, there is a need to develop and implement quantitative methods to interpret genotoxicity dose-response data for risk assessment and regulatory decision-making. Standardized methods to analyze dose-response data, and determine point-of-departure (PoD) metrics, have been established; the most robust PoD is the benchmark dose (BMD). However, there are no standards for regulatory interpretation of mutagenicity BMDs. Although 5-10% is often used as a critical effect size (CES) for BMD determination, values for genotoxicity endpoints have not been established. The use of BMDs to determine health-based guidance values (HBGVs) requires assessment factors (AFs) to account for interspecies differences and variability in human sensitivity. Default AFs used for other endpoints may not be appropriate for interpretation of in vivo mutagenicity BMDs. Analyses of published dose-response data showing the effects of compensatory pathway deficiency indicate that AFs for sensitivity differences should be in the range of 2-20. Additional analyses indicate that the AF to compensate for short treatment durations should be in the range of 5-15. Future work should use available data to empirically determine endpoint-specific CES values; similarly, to determine AF values for BMD adjustment. Future work should also evaluate the ability to use in vitro dose-response data for risk assessment, and the utility of probabilistic methods for determination of mutagenicity HBGVs. Environ. Mol. Mutagen. 61:66-83, 2020. © 2019 Her Majesty the Queen in Right of Canada.

Empirical analysis of BMD metrics in genetic toxicology part II: in vivo potency comparisons to promote reductions in the use of experimental animals for genetic toxicity assessment.

Genotoxicity tests have traditionally been used only for hazard identification, with qualitative dichotomous groupings being used to identify compounds that have the capacity to induce mutations and/or cytogenetic alterations. However, there is an increasing interest in employing quantitative analysis of in vivo dose-response data to derive point of departure (PoD) metrics that can be used to establish human exposure limits or margins of exposure (MOEs), thereby supporting human health risk assessments and regulatory decisions. This work is an extension of our companion article on in vitro dose-response analyses and outlines how the combined benchmark dose (BMD) approach across included covariates can be used to improve the analyses and interpretation of in vivo genetic toxicity dose-response data. Using the BMD-covariate approach, we show that empirical comparisons of micronucleus frequency dose-response data across multiple studies justifies dataset merging, with subsequent analyses improving the precision of BMD estimates and permitting attendant potency ranking of seven clastogens. Similarly, empirical comparisons of Pig-a mutant phenotype frequency data collected in males and females justified dataset merging across sex. This permitted more effective scrutiny regarding the effect of post-exposure sampling time on the mutagenicity of N-ethyl-N-nitrosourea observed in reticulocytes and erythrocytes in the Pig-a assay. The BMD-covariate approach revealed tissue-specific differences in the induction of lacZ transgene mutations in Muta™Mouse specimens exposed to benzo[a]pyrene (BaP), with the results permitting the formulation of mechanistic hypotheses regarding the observed potency ranking. Lastly, we illustrate how historical dose-response data for assessments that examined numerous doses (i.e. induced lacZ mutant frequency (MF) across 10 doses of BaP) can be used to improve the precision of BMDs derived from datasets with far fewer doses (i.e. lacZ MF for 3 doses of dibenz[a,h]anthracene). Collectively, the presented examples illustrate how innovative use of the BMD approach can permit refinement of the use of in vivo data; improving the efficacy of experimental animal use in genetic toxicology without sacrificing PoD precision.

Cancer risk assessment of polycyclic aromatic hydrocarbon contaminated soils determined using bioassay-derived levels of benzo[a]pyrene equivalents.

Here we evaluate the excess lifetime cancer risk (ELCR) posed by 10 PAH-contaminated soils using (i) the currently advocated, targeted chemical-specific approach that assumes dose additivity for carcinogenic PAHs and (ii) a bioassay-based approach that employs the in vitro mutagenic activity of the soil fractions to determine levels of benzo[a]pyrene equivalents and, by extension, ELCR. Mutagenic activity results are presented in our companion paper.1 The results show that ELCR values for the PAH-containing fractions, determined using the chemical-specific approach, are generally (i.e., 8 out of 10) greater than those calculated using the bioassay-based approach; most are less than 5-fold greater. Only two chemical-specific ELCR estimates are less than their corresponding bioassay-derived values; differences are less than 10%. The bioassay-based approach, which permits estimation of ELCR without a priori knowledge of mixture composition, proved to be a useful tool to evaluate the chemical-specific approach. The results suggest that ELCR estimates for complex PAH mixtures determined using a targeted, chemical-specific approach are reasonable, albeit conservative. Calculated risk estimates still depend on contentious PEFs and cancer slope factors. Follow-up in vivo mutagenicity assessments will be required to validate the results and their relevance for human health risk assessment of PAH-contaminated soils.