Search

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 [ABSTRACT FROM AUTHOR]

We recently published a next generation framework for assessing the risk of genomic damage via exposure to chemical substances. The framework entails a systematic approach with the aim to quantify risk levels for substances that induce genomic damage contributing to human adverse health outcomes. Here, we evaluated the utility of the framework for assessing the risk for industrial chemicals, using the case of benzene. Benzene is a well‐studied substance that is generally considered a genotoxic carcinogen and is known to cause leukemia. The case study limits its focus on occupational and general population health as it relates to benzene exposure. Using the framework as guidance, available data on benzene considered relevant for assessment of genetic damage were collected. Based on these data, we were able to conduct quantitative analyses for relevant data sets to estimate acceptable exposure levels and to characterize the risk of genetic damage. Key observations include the need for robust exposure assessments, the importance of information on toxicokinetic properties, and the benefits of cheminformatics. The framework points to the need for further improvement on understanding of the mechanism(s) of action involved, which would also provide support for the use of targeted tests rather than a prescribed set of assays. Overall, this case study demonstrates the utility of the next generation framework to quantitatively model human risk on the basis of genetic damage, thereby enabling a new, innovative risk assessment concept. Environ. Mol. Mutagen. 61:94–113, 2020. © 2019 The Authors. Environmental and Molecular Mutagenesis published by Wiley Periodicals, Inc. on behalf of Environmental Mutagen Society. [ABSTRACT FROM AUTHOR]

Mutations induced in somatic cells and germ cells are responsible for a variety of human diseases, and mutation per se has been considered an adverse health concern since the early part of the 20th Century. Although in vitro and in vivo somatic cell mutation data are most commonly used by regulatory agencies for hazard identification, that is, determining whether or not a substance is a potential mutagen and carcinogen, quantitative mutagenicity dose–response data are being used increasingly for risk assessments. Efforts are currently underway to both improve the measurement of mutations and to refine the computational methods used for evaluating mutation data. We recommend continuing the development of these approaches with the objective of establishing consensus regarding the value of including the quantitative analysis of mutation per se as a required endpoint for comprehensive assessments of toxicological risk. Environ. Mol. Mutagen. 61:34–41, 2020. © 2019 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

The article presents the author's views on policy decisions and research in economics and industrial relations. Scholars in the field of industrial relations have ever been self-conscious about the value of their research output. Perhaps this insecurity stems from the relative youth of the field as a scholarly discipline, the relative age of the scholars within the discipline, or from a feeling of isolation from their mother disciplines. Researchers found a major deficiency in industrial relations research in its tendency to follow the headlines. Economist Milton Derber returned to this theme in 1968, finding confirmation of the topical nature of industrial relations research in the research reports of scholars to the journal Industrial and Labor Relations Review. In spite of the effort of industrial relations researchers to focus on changing policy issues, the tenor of much of the continuing criticism has been that industrial relations research has contributed little to the formation of public policy on issues falling within its jurisdictional domain. The most devastating attack along this line is that of economist John T. Dunlop in the paper under discussion.

For several decades, regulatory testing schemes for genetic damage have been standardized where the tests being utilized examined mutations and structural and numerical chromosomal damage. This has served the genetic toxicity community well when most of the substances being tested were amenable to such assays. The outcome from this testing is usually a dichotomous (yes/no) evaluation of test results, and in many instances, the information is only used to determine whether a substance has carcinogenic potential or not. Over the same time period, mechanisms and modes of action (MOAs) that elucidate a wider range of genomic damage involved in many adverse health outcomes have been recognized. In addition, a paradigm shift in applied genetic toxicology is moving the field toward a more quantitative dose-response analysis and point-of-departure (PoD) determination with a focus on risks to exposed humans. This is directing emphasis on genomic damage that is likely to induce changes associated with a variety of adverse health outcomes. This paradigm shift is moving the testing emphasis for genetic damage from a hazard identification only evaluation to a more comprehensive risk assessment approach that provides more insightful information for decision makers regarding the potential risk of genetic damage to exposed humans. To enable this broader context for examining genetic damage, a next generation testing strategy needs to take into account a broader, more flexible approach to testing, and ultimately modeling, of genomic damage as it relates to human exposure. This is consistent with the larger risk assessment context being used in regulatory decision making. As presented here, this flexible approach for examining genomic damage focuses on testing for relevant genomic effects that can be, as best as possible, associated with an adverse health effect. The most desired linkage for risk to humans would be changes in loci associated with human diseases, whether in somatic or germ cells. The outline of a flexible approach and associated considerations are presented in a series of nine steps, some of which can occur in parallel, which was developed through a collaborative effort by leading genetic toxicologists from academia, government, and industry through the International Life Sciences Institute (ILSI) Health and Environmental Sciences Institute (HESI) Genetic Toxicology Technical Committee (GTTC). The ultimate goal is to provide quantitative data to model the potential risk levels of substances, which induce genomic damage contributing to human adverse health outcomes. Any good risk assessment begins with asking the appropriate risk management questions in a planning and scoping effort. This step sets up the problem to be addressed (e.g., broadly, does genomic damage need to be addressed, and if so, how to proceed). The next two steps assemble what is known about the problem by building a knowledge base about the substance of concern and developing a rational biological argument for why testing for genomic damage is needed or not. By focusing on the risk management problem and potential genomic damage of concern, the next step of assay(s) selection takes place. The work-up of the problem during the earlier steps provides the insight to which assays would most likely produce the most meaningful data. This discussion does not detail the wide range of genomic damage tests available, but points to types of testing systems that can be very useful. Once the assays are performed and analyzed, the relevant data sets are selected for modeling potential risk. From this point on, the data are evaluated and modeled as they are for any other toxicology endpoint. Any observed genomic damage/effects (or genetic event(s)) can be modeled via a dose-response analysis and determination of an estimated PoD. When a quantitative risk analysis is needed for decision making, a parallel exposure assessment effort is performed (exposure assessment is not detailed here as this is not the focus of this discussion; guidelines for this assessment exist elsewhere). Then the PoD for genomic damage is used with the exposure information to develop risk estimations (e.g., using reference dose (RfD), margin of exposure (MOE) approaches) in a risk characterization and presented to risk managers for informing decision making. This approach is applicable now for incorporating genomic damage results into the decision-making process for assessing potential adverse outcomes in chemically exposed humans and is consistent with the ILSI HESI Risk Assessment in the 21st Century (RISK21) roadmap. This applies to any substance to which humans are exposed, including pharmaceuticals, agricultural products, food additives, and other chemicals. It is time for regulatory bodies to incorporate the broader knowledge and insights provided by genomic damage results into the assessments of risk to more fully understand the potential of adverse outcomes in chemically exposed humans, thus improving the assessment of risk due to genomic damage. The historical use of genomic damage data as a yes/no gateway for possible cancer risk has been too narrowly focused in risk assessment. The recent advances in assaying for and understanding genomic damage, including eventually epigenetic alterations, obviously add a greater wealth of information for determining potential risk to humans. Regulatory bodies need to embrace this paradigm shift from hazard identification to quantitative analysis and to incorporate the wider range of genomic damage in their assessments of risk to humans. The quantitative analyses and methodologies discussed here can be readily applied to genomic damage testing results now. Indeed, with the passage of the recent update to the Toxic Substances Control Act (TSCA) in the US, the new generation testing strategy for genomic damage described here provides a regulatory agency (here the US Environmental Protection Agency (EPA), but suitable for others) a golden opportunity to reexamine the way it addresses risk-based genomic damage testing (including hazard identification and exposure). Environ. Mol. Mutagen. 58:264-283, 2017. © 2016 The Authors. Environmental and Molecular Mutagenesis Published by Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]