J. Craig Rowlands

Incorporating new technologies into toxicity testing and risk assessment: moving from 21st century vision to a data-driven framework.

Based on existing data and previous work, a series of studies is proposed as a basis toward a pragmatic early step in transforming toxicity testing. These studies were assembled into a data-driven framework that invokes successive tiers of testing with margin of exposure (MOE) as the primary metric. The first tier of the framework integrates data from high-throughput in vitro assays, in vitro-to-in vivo extrapolation (IVIVE) pharmacokinetic modeling, and exposure modeling. The in vitro assays are used to separate chemicals based on their relative selectivity in interacting with biological targets and identify the concentration at which these interactions occur. The IVIVE modeling converts in vitro concentrations into external dose for calculation of the point of departure (POD) and comparisons to human exposure estimates to yield a MOE. The second tier involves short-term in vivo studies, expanded pharmacokinetic evaluations, and refined human exposure estimates. The results from the second tier studies provide more accurate estimates of the POD and the MOE. The third tier contains the traditional animal studies currently used to assess chemical safety. In each tier, the POD for selective chemicals is based primarily on endpoints associated with a proposed mode of action, whereas the POD for nonselective chemicals is based on potential biological perturbation. Based on the MOE, a significant percentage of chemicals evaluated in the first 2 tiers could be eliminated from further testing. The framework provides a risk-based and animal-sparing approach to evaluate chemical safety, drawing broadly from previous experience but incorporating technological advances to increase efficiency.

Cross-species Comparisons of Transcriptomic Alterations in Human and Rat Primary Hepatocytes Exposed to 2,3,7,8-Tetrachlorodibenzo-p-dioxin

A toxicogenomics approach was used to qualitatively and quantitatively compare the gene expression changes in human and rat primary hepatocytes exposed to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). Hepatocytes from five individual rats and five individual humans were exposed for 24 h to 11 concentrations of TCDD ranging from 0.00001 to 100nM and a vehicle control. Gene expression changes were analyzed using whole-genome microarrays containing 13,002 orthologs. Significant changes in expression of individual orthologs at any concentration (fold change [FC] ± 1.5 and false discovery rate < 0.05) were higher in the rat (1547) compared with human hepatocytes (475). Only 158 differentially expressed orthologs were common between rats and humans. Enrichment analysis was performed on the differentially expressed orthologs in each species with 49 and 34 enriched human and rat pathways, respectively. Only 12 enriched pathways were shared between the two species. The results demonstrate significant cross-species differences in expression at both the gene and pathway level. Benchmark dose analysis of gene expression changes showed an average 18-fold cross-species difference in potency among differentially expressed orthologs with the rat more sensitive than the human. Similar cross-species differences in potency were observed for signaling pathways. Using the maximum FC in gene expression as a measure of efficacy, the human hepatocytes showed on average a 20% lower efficacy among the individual orthologs showing differential expression. The results provide evidence for divergent cross-species gene expression changes in response to TCDD and are consistent with epidemiological and clinical evidence showing humans to be less sensitive to TCDD-induced hepatotoxicity.

A 21st century roadmap for human health risk assessment

Abstract The Health and Environmental Sciences Institute (HESI)-coordinated Risk Assessment in the 21st Century (RISK21) project was initiated to develop a scientific, transparent, and efficient approach to the evolving world of human health risk assessment, and involved over 120 participants from 12 countries, 15 government institutions, 20 universities, 2 non-governmental organizations, and 12 corporations. This paper provides a brief overview of the tiered RISK21 framework called the roadmap and risk visualization matrix, and articulates the core principles derived by RISK21 participants that guided its development. Subsequent papers describe the roadmap and matrix in greater detail. RISK21 principles include focusing on problem formulation, utilizing existing information, starting with exposure assessment (rather than toxicity), and using a tiered process for data development. Bringing estimates of exposure and toxicity together on a two-dimensional matrix provides a clear rendition of human safety and risk. The value of the roadmap is its capacity to chronicle the stepwise acquisition of scientific information and display it in a clear and concise fashion. Furthermore, the tiered approach and transparent display of information will contribute to greater efficiencies by calling for data only as needed (enough precision to make a decision), thus conserving animals and other resources.

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.

Risk assessment in the 21st century: roadmap and matrix.

Abstract The RISK21 integrated evaluation strategy is a problem formulation-based exposure-driven risk assessment roadmap that takes advantage of existing information to graphically represent the intersection of exposure and toxicity data on a highly visual matrix. This paper describes in detail the process for using the roadmap and matrix. The purpose of this methodology is to optimize the use of prior information and testing resources (animals, time, facilities, and personnel) to efficiently and transparently reach a risk and/or safety determination. Based on the particular problem, exposure and toxicity data should have sufficient precision to make such a decision. Estimates of exposure and toxicity, bounded by variability and/or uncertainty, are plotted on the X- and Y-axes of the RISK21 matrix, respectively. The resulting intersection is a highly visual representation of estimated risk. Decisions can then be made to increase precision in the exposure or toxicity estimates or declare that the available information is sufficient. RISK21 represents a step forward in the goal to introduce new methodologies into 21st century risk assessment. Indeed, because of its transparent and visual process, RISK21 has the potential to widen the scope of risk communication beyond those with technical expertise.

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.

AH receptor agonist activity in human blood measured with a cell-based bioassay: Evidence for naturally occurring AH receptor ligands in vivo

In the present study, an aryl hydrocarbon receptor (AHR)-driven reporter gene bioassay was used to measure the activity, measured as an induction equivalent (IEQ) as compared to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), or IEQ concentration in human blood samples from 10 volunteers under different dietary regimens. Blood concentrations of polychlorinated dibenzo-p-dioxins/furans (PCDD/Fs) and polychlorinated biphenyls (PCBs), as determined by analytical chemistry (HR-GC/MS), and expressed as toxic equivalents (TEQs) with the use of TCDD equivalency factors (TEFs), were within a range that has been reported in the general US population, ranging from 0.022 to 0.119 ppt (whole blood basis). However, the human blood IEQ measured directly via bioassay ranged from 13.4 to 218 ppt (whole blood basis). These order of magnitude greater IEQs compared to the TEQs for dioxins, furans, and certain PCBs suggests that human blood contains a relatively high level of AHR agonists able to activate the CYP1A1 dioxin response element (DRE)-linked reporter gene bioassay and that this AHR activity is not accounted for by PCDDs/Fs and dioxin-like PCBs based on standard HR-GC/MS and TEF analysis. When study participants switched from a “baseline” to a high-vegetable diet, increases in bioassay IEQ were observed that were statistically significant (P<0.05). In addition, IEQ activity was elevated above levels observed following dietary intervention in two subjects given indole-3-carbinol (I3C) supplements. We conclude that a substantial portion of the IEQ activity occurred as a result of the increased intake of natural AHR agonists (NAHRAs) present in many fruits, vegetables. and herbs. Our findings also suggest that dietary NAHRAs constitute a substantial daily dietary intake of AHR-active compounds, and these NAHRAs could influence AHR status in humans and play a role in a basal level of AHR activation.

Knockout of the aryl hydrocarbon receptor results in distinct hepatic and renal phenotypes in rats and mice

The aryl hydrocarbon receptor (AHR) is a ligand-activated transcription factor which plays a role in the development of multiple tissues and is activated by a large number of ligands, including 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). In order to examine the roles of the AHR in both normal biological development and response to environmental chemicals, an AHR knockout (AHR-KO) rat model was created and compared with an existing AHR-KO mouse. AHR-KO rats harboring either 2-bp or 29-bp deletion mutation in exon 2 of the AHR were created on the Sprague-Dawley genetic background using zinc-finger nuclease (ZFN) technology. Rats harboring either mutation type lacked expression of AHR protein in the liver. AHR-KO rats were also insensitive to thymic involution, increased hepatic weight and the induction of AHR-responsive genes (Cyp1a1, Cyp1a2, Cyp1b1, Ahrr) following acute exposure to 25 μg/kg TCDD. AHR-KO rats had lower basal expression of transcripts for these genes and also accumulated ~30-45-fold less TCDD in the liver at 7 days post-exposure. In untreated animals, AHR-KO mice, but not AHR-KO rats, had alterations in serum analytes indicative of compromised hepatic function, patent ductus venosus of the liver and persistent hyaloid arteries in the eye. AHR-KO rats, but not AHR-KO mice, displayed pathological alterations to the urinary tract: bilateral renal dilation (hydronephrosis), secondary medullary tubular and uroepithelial degenerative changes and bilateral ureter dilation (hydroureter). The present data indicate that the AHR may play significantly different roles in tissue development and homeostasis and toxicity across rodent species.

2-(4-Amino-3-methylphenyl)-5-fluorobenzothiazole is a ligand and shows species-specific partial agonism of the aryl hydrocarbon receptor.

2-(4-Amino-3-methylphenyl)-5-fluorobenzothiazole (5F 203) and related compounds are a series of anti-cancer candidate pharmaceuticals, that have been shown to activate the AhR. We show that these compounds are high-affinity ligands for the rat AhR, but a quantitative assay for their ability to induce CYP1A1 RNA in H4IIEC3 cells, a measure of activation of the AhR, showed a poor relationship between affinity for the AhR and ability to induce CYP1A1 RNA. 5F 203, an agonist with low potency, was able to antagonise the induction of CYP1A1 RNA by TCDD, while IH 445, a potent agonist, did not antagonise the induction of CYP1A1 RNA by TCDD, and Schild analysis confirmed 5F 203 to be a potent antagonist of the induction of CYP1A1 RNA by TCDD in H4IIEC3 cells. In contrast, several benzothiazoles show potent induction of CYP1A1 RNA in human MCF-7 cells, and 5F 203 is unable to detectably antagonise the induction of CYP1A1 RNA in MCF-7 cells, showing a species difference in antagonism. Evaluation of the anti-proliferative activity of benzothiazoles showed that the ability to agonise the AhR correlated with growth inhibition both in H4IIEC3 cells for a variety of benzothiazoles, and between H4IIEC3 and MCF-7 cells for 5F 203, suggesting an important role of agonism of the AhR in the anti-proliferative activity of benzothiazoles.

Developing scientific confidence in HTS-derived prediction models: lessons learned from an endocrine case study.

High throughput (HTS) and high content (HCS) screening methods show great promise in changing how hazard and risk assessments are undertaken, but scientific confidence in such methods and associated prediction models needs to be established prior to regulatory use. Using a case study of HTS-derived models for predicting in vivo androgen (A), estrogen (E), thyroid (T) and steroidogenesis (S) endpoints in endocrine screening assays, we compare classification (fitting) models to cross validation (prediction) models. The more robust cross validation models (based on a set of endocrine ToxCast™ assays and guideline in vivo endocrine screening studies) have balanced accuracies from 79% to 85% for A and E, but only 23% to 50% for T and S. Thus, for E and A, HTS results appear promising for initial use in setting priorities for endocrine screening. However, continued research is needed to expand the domain of applicability and to develop more robust HTS/HCS-based prediction models prior to their use in other regulatory applications. Based on the lessons learned, we propose a framework for documenting scientific confidence in HTS assays and the prediction models derived therefrom. The documentation, transparency and the scientific rigor involved in addressing the elements in the proposed Scientific Confidence Framework could aid in discussions and decisions about the prediction accuracy needed for different applications.