Commentary: Value of information case study strongly supports use of the Threshold of Toxicological Concern (TTC).

A Value of Information (VOI) analysis can play a key role in decision-making for adopting new approach methodologies (NAMs). We applied EPA's recently developed VOI framework to the Threshold of Toxicological Concern (TTC). Obtaining/deriving a TTC value for use as a toxicity reference value (TRV) for substances with limited toxicity data was shown to provide equivalent or greater health protection, immense return on investment (ROI), greater net benefit, and substantially lower costs of delay (CoD) compared with TRVs derived from either traditional human health assessment (THHA) chronic toxicity testing in lab animals or the 5-day in vivo EPA Transcriptomic Assessment Product (ETAP). For all nine exposure scenarios examined, the TTC was more economical terms of CoD and ROI than the ETAP or the THHA; expected net benefit was similar for the TTC and ETAP with both of these more economical than the THHA The TTC ROI was immensely greater (5,000,000-fold on average) than the ROI for THHA and the ETAP ROI (100,000-fold on average). These results support the use of the TTC for substances within its domain of applicability to waive requiring certain in vivo tests, or at a minimum, as an initial screening step before conducting either the ETAP or THHA in vivo studies.

Species differences in specific ligand-binding affinity and activation of AHR: The biological basis for calculation of relative effective potencies and toxic equivalence factors.

In 2022 the World Health Organization (WHO) published updated 'Toxic Equivalence Factors' (TEFs) for a wide variety of chlorinated dioxins, dibenzofurans and PCBs [collectively referred to as 'dioxin-like chemicals'; DLCs) that interact with the aryl hydrocarbon receptor (AHR)]. Their update used sophisticated statistical analysis of hundreds of published studies that reported estimation of 'Relative Effective Potency' (REP) values for individual DLC congeners. The weighting scheme used in their assessment of each study favored in vivo over in vitro studies and was based largely on rodent studies. In this Commentary, we highlight the large body of published studies that demonstrate large species differences in AHR-ligand activation and provide supporting evidence for our position that the WHO 2022 TEF values intended for use in human risk assessment of DLC mixtures will provide highly misleading overestimates of 'Toxic Equivalent Quotients' (TEQs), because of well-recognized striking differences in AHR ligand affinities between rodent (rat, mouse) and human. The data reviewed in our Commentary support the position that human tissue-derived estimates of REP/TEF values for individual DLC congeners, although uncertain, will provide much better, more realistic estimates of potential activation of the human AHR, when exposure to complex DLC mixtures occurs.

Providing context for phosphatidylethanol as a biomarker of alcohol consumption with a pharmacokinetic model.

Phosphatidylethanol (PEth) is increasingly used as a biomarker of heavy drinking. Many different forms of PEth can form in red blood cell membranes from the action of the enzyme phospholipase D. PEth has a very long duration in blood because, in contrast to other tissues, RBCs lack the enzymes that degrade PEth. Because this biomarker is relatively new, interpretations of the analytical measurements of PEth may be misinterpreted and the resulting predictions of actual alcohol consumption inaccurate. Hence, a simple pharmacokinetic model of PEth was developed to provide a means of contextualizing these analytical results. A number of alcohol consumption scenarios and current clinical screening levels were examined with the model.

How well can carcinogenicity be predicted by high throughput "characteristics of carcinogens" mechanistic data?

IARC has begun using ToxCast/Tox21 data in efforts to represent key characteristics of carcinogens to organize and weigh mechanistic evidence in cancer hazard determinations and this implicit inference approach also is being considered by USEPA. To determine how well ToxCast/Tox21 data can explicitly predict cancer hazard, this approach was evaluated with statistical analyses and machine learning prediction algorithms. Substances USEPA previously classified as having cancer hazard potential were designated as positives and substances not posing a carcinogenic hazard were designated as negatives. Then ToxCast/Tox21 data were analyzed both with and without adjusting for the cytotoxicity burst effect commonly observed in such assays. Using the same assignments as IARC of ToxCast/Tox21 assays to the seven key characteristics of carcinogens, the ability to predict cancer hazard for each key characteristic, alone or in combination, was found to be no better than chance. Hence, we have little scientific confidence in IARC's inference models derived from current ToxCast/Tox21 assays for key characteristics to predict cancer. This finding supports the need for a more rigorous mode-of-action pathway-based framework to organize, evaluate, and integrate mechanistic evidence with animal toxicity, epidemiological investigations, and knowledge of exposure and dosimetry to evaluate potential carcinogenic hazards and risks to humans.

Bayesian methods for uncertainty factor application for derivation of reference values.

In 2014, the National Research Council (NRC) published Review of EPA's Integrated Risk Information System (IRIS) Process that considers methods EPA uses for developing toxicity criteria for non-carcinogens. These criteria are the Reference Dose (RfD) for oral exposure and Reference Concentration (RfC) for inhalation exposure. The NRC Review suggested using Bayesian methods for application of uncertainty factors (UFs) to adjust the point of departure dose or concentration to a level considered to be without adverse effects for the human population. The NRC foresaw Bayesian methods would be potentially useful for combining toxicity data from disparate sources-high throughput assays, animal testing, and observational epidemiology. UFs represent five distinct areas for which both adjustment and consideration of uncertainty may be needed. NRC suggested UFs could be represented as Bayesian prior distributions, illustrated the use of a log-normal distribution to represent the composite UF, and combined this distribution with a log-normal distribution representing uncertainty in the point of departure (POD) to reflect the overall uncertainty. Here, we explore these suggestions and present a refinement of the methodology suggested by NRC that considers each individual UF as a distribution. From an examination of 24 evaluations from EPA's IRIS program, when individual UFs were represented using this approach, the geometric mean fold change in the value of the RfD or RfC increased from 3 to over 30, depending on the number of individual UFs used and the sophistication of the assessment. We present example calculations and recommendations for implementing the refined NRC methodology.

The adverse outcome pathway for rodent liver tumor promotion by sustained activation of the aryl hydrocarbon receptor.

An Adverse Outcome Pathway (AOP) represents the existing knowledge of a biological pathway leading from initial molecular interactions of a toxicant and progressing through a series of key events (KEs), culminating with an apical adverse outcome (AO) that has to be of regulatory relevance. An AOP based on the mode of action (MOA) of rodent liver tumor promotion by dioxin-like compounds (DLCs) has been developed and the weight of evidence (WoE) of key event relationships (KERs) evaluated using evolved Bradford Hill considerations. Dioxins and DLCs are potent aryl hydrocarbon receptor (AHR) ligands that cause a range of species-specific adverse outcomes. The occurrence of KEs is necessary for inducing downstream biological responses and KEs may occur at the molecular, cellular, tissue and organ levels. The common convention is that an AOP begins with the toxicant interaction with a biological response element; for this AOP, this initial event is binding of a DLC ligand to the AHR. Data from mechanistic studies, lifetime bioassays and approximately thirty initiation-promotion studies have established dioxin and DLCs as rat liver tumor promoters. Such studies clearly show that sustained AHR activation, weeks or months in duration, is necessary to induce rodent liver tumor promotion--hence, sustained AHR activation is deemed the molecular initiating event (MIE). After this MIE, subsequent KEs are 1) changes in cellular growth homeostasis likely associated with expression changes in a number of genes and observed as development of hepatic foci and decreases in apoptosis within foci; 2) extensive liver toxicity observed as the constellation of effects called toxic hepatopathy; 3) cellular proliferation and hyperplasia in several hepatic cell types. This progression of KEs culminates in the AO, the development of hepatocellular adenomas and carcinomas and cholangiolar carcinomas. A rich data set provides both qualitative and quantitative knowledge of the progression of this AOP through KEs and the KERs. Thus, the WoE for this AOP is judged to be strong. Species-specific effects of dioxins and DLCs are well known--humans are less responsive than rodents and rodent species differ in sensitivity between strains. Consequently, application of this AOP to evaluate potential human health risks must take these differences into account.

An exposure:activity profiling method for interpreting high-throughput screening data for estrogenic activity--proof of concept.

Rapid high throughput in vitro screening (HTS) assays are now available for characterizing dose-responses in assays that have been selected for their sensitivity in detecting estrogen-related endpoints. For example, EPA's ToxCast™ program recently released endocrine assay results for more than 1800 substances and the interagency Tox21 consortium is in the process of releasing data for approximately 10,000 chemicals. But such activity measurements alone fall short for the purposes of priority setting or screening because the relevant exposure context is not considered. Here, we extend the method of exposure:activity profiling by calculating the exposure:activity ratios (EARs) using human exposure estimates and AC50 values for a range of chemicals tested in a suite of seven estrogenic assays in ToxCast™ and Tox21. To provide additional context, relative estrogenic exposure:activity quotients (REEAQ) were derived by comparing chemical-specific EARs to the EAR of the ubiquitous dietary phytoestrogen, genistein (GEN). Although the activity of a substance in HTS-endocrine assays is not a measure of health hazard or risk, understanding how such a dose compares to human exposures provides a valuable additional metric that can be used in decision-making; substances with small EARs and REEAQs would indicate low priority for further endocrine screening or testing.

Proposing a scientific confidence framework to help support the application of adverse outcome pathways for regulatory purposes.

An adverse outcome pathway (AOP) describes the causal linkage between initial molecular events and an adverse outcome at individual or population levels. Whilst there has been considerable momentum in AOP development, far less attention has been paid to how AOPs might be practically applied for different regulatory purposes. This paper proposes a scientific confidence framework (SCF) for evaluating and applying a given AOP for different regulatory purposes ranging from prioritizing chemicals for further evaluation, to hazard prediction, and ultimately, risk assessment. The framework is illustrated using three different AOPs for several typical regulatory applications. The AOPs chosen are ones that have been recently developed and/or published, namely those for estrogenic effects, skin sensitisation, and rodent liver tumor promotion. The examples confirm how critical the data-richness of an AOP is for driving its practical application. In terms of performing risk assessment, human dosimetry methods are necessary to inform meaningful comparisons with human exposures; dosimetry is applied to effect levels based on non-testing approaches and in vitro data. Such a comparison is presented in the form of an exposure:activity ratio (EAR) to interpret biological activity in the context of exposure and to provide a basis for product stewardship and regulatory decision making.

The use of mode of action information in risk assessment: quantitative key events/dose-response framework for modeling the dose-response for key events.

The HESI RISK21 project formed the Dose-Response/Mode-of-Action Subteam to develop strategies for using all available data (in vitro, in vivo, and in silico) to advance the next-generation of chemical risk assessments. A goal of the Subteam is to enhance the existing Mode of Action/Human Relevance Framework and Key Events/Dose Response Framework (KEDRF) to make the best use of quantitative dose-response and timing information for Key Events (KEs). The resulting Quantitative Key Events/Dose-Response Framework (Q-KEDRF) provides a structured quantitative approach for systematic examination of the dose-response and timing of KEs resulting from a dose of a bioactive agent that causes a potential adverse outcome. Two concepts are described as aids to increasing the understanding of mode of action-Associative Events and Modulating Factors. These concepts are illustrated in two case studies; 1) cholinesterase inhibition by the pesticide chlorpyrifos, which illustrates the necessity of considering quantitative dose-response information when assessing the effect of a Modulating Factor, that is, enzyme polymorphisms in humans, and 2) estrogen-induced uterotrophic responses in rodents, which demonstrate how quantitative dose-response modeling for KE, the understanding of temporal relationships between KEs and a counterfactual examination of hypothesized KEs can determine whether they are Associative Events or true KEs.

Use and validation of HT/HC assays to support 21st century toxicity evaluations.

Advances in high throughput and high content (HT/HC) methods such as those used in the fields of toxicogenomics, bioinformatics, and computational toxicology have the potential to improve both the efficiency and effectiveness of toxicity evaluations and risk assessments. However, prior to use, scientific confidence in these methods should be formally established. Traditional validation approaches that define relevance, reliability, sensitivity and specificity may not be readily applicable. HT/HC methods are not exact replacements for in vivo testing, and although run individually, these assays are likely to be used as a group or battery for decision making and use robotics, which may be unique in each laboratory setting. Building on the frameworks developed in the 2010 Institute of Medicine Report on Biomarkers and the OECD 2007 Report on (Q)SAR Validation, we present constructs that can be adapted to address the validation challenges of HT/HC methods. These are flexible, transparent, and require explicit specification of context and purpose of use such that scientific confidence (validation) can be defined to meet different regulatory applications. Using these constructs, we discuss how anchoring the assays and their prediction models to Adverse Outcome Pathways (AOPs) could facilitate the interpretation of results and support scientifically defensible fit-for-purpose applications.

Utilizing Threshold of Toxicological Concern (TTC) with High Throughput Exposure Predictions (HTE) as a Risk-Based Prioritization Approach for thousands of chemicals.

Regulatory agencies across the world are facing the challenge of performing risk-based prioritization of thousands of chemicals in commerce. Here, we present an approach using the Threshold of Toxicological Concern (TTC) combined with heuristic high-throughput exposure (HTE) modelling to rank order chemicals for further evaluation. Accordingly, for risk-based prioritization, chemicals with exposures > TTC would be ranked as higher priority for further evaluation whereas substances with exposures < TTC would be ranked as lower priority. An initial proof of concept, using a dataset of 7986 substances with previously modeled median and upper 95% credible interval (UCI) total daily median exposure rates showed fewer than 5% of substances had UCI exposures > the Cramer Class III TTC (1.5 µg/kg-day). We extended the analysis by profiling the same dataset through the TTC workflow published by Kroes et al (2004) which accounts for known exclusions to the TTC as well as structural alerts. UCI exposures were then compared to the appropriate class-specific TTC. None of the substances categorized as Cramer Class I or Cramer Class II exceeded their respective TTC values and no more than 2% of substances categorized as Cramer Class III or acetylcholinesterase inhibitors exceeded their respective TTC values. The modeled UCI exposures for the majority of the 1853 chemicals with genotoxicity structural alerts did exceed the TTC of 0.0025 µg/kg-day, but only 79 substances exceeded this TTC if median exposure values were used. For substances for which UCI exposures exceeded relevant TTC values, we highlight possible approaches for consideration to refine the HTE : TTC approach. Overall, coupling TTC with HTE offers promise as a pragmatic first step in ranking substances as part of a risk-based prioritization approach.

In vitro to in vivo extrapolation for high throughput prioritization and decision making.

In vitro chemical safety testing methods offer the potential for efficient and economical tools to provide relevant assessments of human health risk. To realize this potential, methods are needed to relate in vitro effects to in vivo responses, i.e., in vitro to in vivo extrapolation (IVIVE). Currently available IVIVE approaches need to be refined before they can be utilized for regulatory decision-making. To explore the capabilities and limitations of IVIVE within this context, the U.S. Environmental Protection Agency Office of Research and Development and the National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods co-organized a workshop and webinar series. Here, we integrate content from the webinars and workshop to discuss activities and resources that would promote inclusion of IVIVE in regulatory decision-making. We discuss properties of models that successfully generate predictions of in vivo doses from effective in vitro concentration, including the experimental systems that provide input parameters for these models, areas of success, and areas for improvement to reduce model uncertainty. Finally, we provide case studies on the uses of IVIVE in safety assessments, which highlight the respective differences, information requirements, and outcomes across various approaches when applied for decision-making.

Approaches for describing and communicating overall uncertainty in toxicity characterizations: U.S. Environmental Protection Agency's Integrated Risk Information System (IRIS) as a case study.

Single point estimates of human health hazard/toxicity values such as a reference dose (RfD) are generally used in chemical hazard and risk assessment programs for assessing potential risks associated with site- or use-specific exposures. The resulting point estimates are often used by risk managers for regulatory decision-making, including standard setting, determination of emission controls, and mitigation of exposures to chemical substances. Risk managers, as well as stakeholders (interested and affected parties), often have limited information regarding assumptions and uncertainty factors in numerical estimates of both hazards and risks. Further, the use of different approaches for addressing uncertainty, which vary in transparency, can lead to a lack of confidence in the scientific underpinning of regulatory decision-making. The overarching goal of this paper, which was developed from an invited participant workshop, is to offer five approaches for presenting toxicity values in a transparent manner in order to improve the understanding, consideration, and informed use of uncertainty by risk assessors, risk managers, and stakeholders. The five approaches for improving the presentation and communication of uncertainty are described using U.S. Environmental Protection Agency's (EPA's) Integrated Risk Information System (IRIS) as a case study. These approaches will ensure transparency in the documentation, development, and use of toxicity values at EPA, the Agency for Toxic Substances and Disease Registry (ATSDR), and other similar assessment programs in the public and private sector. Further empirical testing will help to inform the approaches that will work best for specific audiences and situations.

A model for aryl hydrocarbon receptor-activated gene expression shows potency and efficacy changes and predicts squelching due to competition for transcription co-activators.

A stochastic model of nuclear receptor-mediated transcription was developed based on activation of the aryl hydrocarbon receptor (AHR) by 2,3,7,8-tetrachlorodibenzodioxin (TCDD) and subsequent binding the activated AHR to xenobiotic response elements (XREs) on DNA. The model was based on effects observed in cells lines commonly used as in vitro experimental systems. Following ligand binding, the AHR moves into the cell nucleus and forms a heterodimer with the aryl hydrocarbon nuclear translocator (ARNT). In the model, a requirement for binding to DNA is that a generic coregulatory protein is subsequently bound to the AHR-ARNT dimer. Varying the amount of coregulator available within the nucleus altered both the potency and efficacy of TCDD for inducing for transcription of CYP1A1 mRNA, a commonly used marker for activation of the AHR. Lowering the amount of available cofactor slightly increased the EC50 for the transcriptional response without changing the efficacy or maximal response. Further reduction in the amount of cofactor reduced the efficacy and produced non-monotonic dose-response curves (NMDRCs) at higher ligand concentrations. The shapes of these NMDRCs were reminiscent of the phenomenon of squelching. Resource limitations for transcriptional machinery are becoming apparent in eukaryotic cells. Within single cells, nuclear receptor-mediated gene expression appears to be a stochastic process; however, intercellular communication and other aspects of tissue coordination may represent a compensatory process to maintain an organism's ability to respond on a phenotypic level to various stimuli within an inconstant environment.

Evidence-based toxicology for the 21st century: opportunities and challenges.

The Evidence-based Toxicology Collaboration (EBTC) was established recently to translate evidence-based approaches from medicine and health care to toxicology in an organized and sustained effort. The EBTC held a workshop on "Evidence-based Toxicology for the 21st Century: Opportunities and Challenges" in Research Triangle Park, North Carolina, USA on January 24-25, 2012. The presentations largely reflected two EBTC priorities: to apply evidence-based methods to assessing the performance of emerging pathway-based testing methods consistent with the 2007 National Research Council report on "Toxicity Testing in the 21st Century" as well as to adopt a governance structure and work processes to move that effort forward. The workshop served to clarify evidence-based approaches and to provide food for thought on substantive and administrative activities for the EBTC. Priority activities include conducting pilot studies to demonstrate the value of evidence-based approaches to toxicology, as well as conducting educational outreach on these approaches.

Just who is at risk? The ethics of environmental regulation.

The willingness to view risk as part of daily life has vanished. A risk-averse mindset among environmental regulators engenders confusion between the ethics of intention and the ethics of consequence, leading to the elevation of the precautionary principle with unintended and often unfortunate outcomes. Environmental risk assessment is conservative, but the actual level of conservatism cannot be determined. High-end exposure assumptions and current toxicity criteria from the USEPA, based on linear extrapolation for carcinogens and default uncertainty factors for systemic toxicants, obscure the degree of conservatism in risk assessments. Ideally, one could choose a percentile of the target population to include within environmental standards, but this choice is complicated by the food, pharmaceutical and advertising industries, whose activities, inadvertent or not, often promote maladaptive and unhealthy lifestyle choices. There has lately been much discussion about background exposures and disease processes and their potential to increase the risk from environmental chemicals. Should these background exposures or disease processes, especially those associated with maladaptive individual choices, be included as part of a regulatory risk evaluation? A significant ethical question is whether environmental regulation should protect those pursuing a self-destructive lifestyle that may add to or synergize with otherwise innocuous environmental exposures. Choosing a target percentile of protection would provide an increased level of transparency and the flexibility to choose a higher or lower percentile if such a choice is warranted. Transparency and flexibility will lead to more responsive environmental regulation that balances protection of public health and the stewardship of societal resources.

Human and rat primary hepatocyte CYP1A1 and 1A2 induction with 2,3,7,8-tetrachlorodibenzo-p-dioxin, 2,3,7,8-tetrachlorodibenzofuran, and 2,3,4,7,8-pentachlorodibenzofuran.

The concentration dose response for aryl hydrocarbon receptor (AHR)-mediated CYP1A1 and CYP1A2 messenger RNA (mRNA) induction and enzyme activity was determined in primary cultures of rat and human hepatocytes for 2,3,7,8-tetrachlorodibenzo-p-dioxin, 2,3,4,7,8-pentachlorodibenzofuran, and 2,3,7,8-tetrachlorodibenzofuran. Eleven different congener concentrations from 0.00001 to 100 nM were used, thus spanning seven orders of magnitude. The Hill model was used to obtain values of EC(x) and maximal response from the individual data sets. No-observed effect concentration values were derived using several statistical methods including Dunnett's test, the Welch-Aspin test, and step-down bilinear regression. Thresholds were estimated using baseline projection methods and a "hockey stick" fitting method. Human hepatocytes were less responsive and less sensitive with respect to CYP1A1 activity and mRNA induction than rats. On the other hand, the human CYP1A2 response was more robust than the response in rats but generally less sensitive. These data allow an evaluation of relative species sensitivities for developing interspecies toxicodynamic adjustment factors, for assessing AHR activation thresholds, and for evaluating relative congener potencies. Overall, these data support the position that humans are less sensitive than rats to these AHR-dependent end points and support the use of a data-derived adjustment factor of 1.0 or less for extrapolating between rats and humans.

Estimates of cancer potency of 2,3,7,8-tetrachlorodibenzo(p)dioxin using linear and nonlinear dose-response modeling and toxicokinetics.

Linear and nonlinear toxicity criteria were derived for 2,3,7,8-tetrachlorodibenzo(p)dioxin (TCDD) using the recent National Toxicology Program rat cancer bioassay. Dose-response relationships were assessed for combined liver tumors based on lifetime average liver concentrations (LALCs) estimated with a toxicokinetic model. Rat LALC estimates at the 1% point of departure (POD) were obtained with benchmark dose (BMD) modeling to yield the BMD(01) in terms of LALC. The same toxicokinetic model was used to back-extrapolate the human-equivalent external dose (HED). A linear cancer slope factor (CSF) with a value of 1 x 10(-4) per pg/kg/day was calculated as the ratio between the benchmark response rate and the HED at the lower confidence limit of the benchmark dose (BMDL)(01). A nonlinear reference dose (RfD) with a value of 100 pg/kg/day was developed from the BMD(01) value by applying uncertainty factors to rat internal and human external doses. The RfD was 100 times higher than the 10(-4) risk-specific dose (RSD) based on the linear CSF. For comparison, BMD(01) and BMDL(01) values were developed for key events in the tumor promotion mode of action (MOA) of TCDD. This MOA involves dysregulation of the normal function of the aryl hydrocarbon receptor and its associated biological processes and results in pathologies that drive tumor promotion and progression. The BMD(01) values for key events were consistent with the timing of the key events within the MOA and provided support for the choices of the 1% tumor rate as a POD and dichotomous Hill model for representing receptor-mediated carcinogenicity. Because a threshold toxicity criterion most accurately reflects the MOA, the RfD for TCDD with a value of 100 pg/kg/day is considered appropriate for regulatory purposes, consistent with a 2006 NRC panel's recommendation to develop a threshold-based cancer potency factor for TCDD and with the methodology in U.S. Environmental Protection Agency's Cancer Guidelines.