Thomas B. Knudsen

In Vitro Screening of Environmental Chemicals for Targeted Testing Prioritization: The ToxCast Project

Background Chemical toxicity testing is being transformed by advances in biology and computer modeling, concerns over animal use, and the thousands of environmental chemicals lacking toxicity data. The U.S. Environmental Protection Agency’s ToxCast program aims to address these concerns by screening and prioritizing chemicals for potential human toxicity using in vitro assays and in silico approaches. Objectives This project aims to evaluate the use of in vitro assays for understanding the types of molecular and pathway perturbations caused by environmental chemicals and to build initial prioritization models of in vivo toxicity. Methods We tested 309 mostly pesticide active chemicals in 467 assays across nine technologies, including high-throughput cell-free assays and cell-based assays, in multiple human primary cells and cell lines plus rat primary hepatocytes. Both individual and composite scores for effects on genes and pathways were analyzed. Results Chemicals displayed a broad spectrum of activity at the molecular and pathway levels. We saw many expected interactions, including endocrine and xenobiotic metabolism enzyme activity. Chemicals ranged in promiscuity across pathways, from no activity to affecting dozens of pathways. We found a statistically significant inverse association between the number of pathways perturbed by a chemical at low in vitro concentrations and the lowest in vivo dose at which a chemical causes toxicity. We also found associations between a small set of in vitro assays and rodent liver lesion formation. Conclusions This approach promises to provide meaningful data on the thousands of untested environmental chemicals and to guide targeted testing of environmental contaminants.

A roadmap for the development of alternative (non-animal) methods for systemic toxicity testing - t4 report

Systemic toxicity testing forms the cornerstone for the safety evaluation of substances. Pressures to move from traditional animal models to novel technologies arise from various concerns, including: the need to evaluate large numbers of previously untested chemicals and new products (such as nanoparticles or cell therapies), the limited predictivity of traditional tests for human health effects, duration and costs of current approaches, and animal welfare considerations. The latter holds especially true in the context of the scheduled 2013 marketing ban on cosmetic ingredients tested for systemic toxicity. Based on a major analysis of the status of alternative methods (Adler et al., 2011) and its independent review (Hartung et al., 2011), the present report proposes a roadmap for how to overcome the acknowledged scientific gaps for the full replacement of systemic toxicity testing using animals. Five whitepapers were commissioned addressing toxicokinetics, skin sensitization, repeated-dose toxicity, carcinogenicity, and reproductive toxicity testing. An expert workshop of 35 participants from Europe and the US discussed and refined these whitepapers, which were subsequently compiled to form the present report. By prioritizing the many options to move the field forward, the expert group hopes to advance regulatory science.

Predictive Model of Rat Reproductive Toxicity from ToxCast High Throughput Screening

The U.S. Environmental Protection Agencys ToxCast research program uses high throughput screening (HTS) for profiling bioactivity and predicting the toxicity of large numbers of chemicals. ToxCast Phase I tested 309 well-characterized chemicals in more than 500 assays for a wide range of molecular targets and cellular responses. Of the 309 environmental chemicals in Phase I, 256 were linked to high-quality rat multigeneration reproductive toxicity studies in the relational Toxicity Reference Database. Reproductive toxicants were defined here as having achieved a reproductive lowest-observed-adverse-effect level of less than 500 mg kg−1 day−1. Eight-six chemicals were identified as reproductive toxicants in the rat, and 68 of those had sufficient in vitro bioactivity to model. Each assay was assessed for univariate association with the identified reproductive toxicants. Significantly associated assays were linked to gene sets and used for the subsequent predictive modeling. Using linear discriminant analysis and fivefold cross-validation, a robust and stable predictive model was produced capable of identifying rodent reproductive toxicants with 77% ± 2% and 74% ± 5% (mean ± SEM) training and test cross-validation balanced accuracies, respectively. With a 21-chemical external validation set, the model was 76% accurate, further indicating the models potential for prioritizing the many thousands of environmental chemicals with little to no hazard information. The biological features of the model include steroidal and nonsteroidal nuclear receptors, cytochrome P450 enzyme inhibition, G protein-coupled receptors, and cell signaling pathway readouts—mechanistic information suggesting additional targeted, integrated testing strategies and potential applications of in vitro HTS to risk assessment.

Zebrafish developmental screening of the ToxCast™ Phase I chemical library

Zebrafish (Danio rerio) is an emerging toxicity screening model for both human health and ecology. As part of the Computational Toxicology Research Program of the U.S. EPA, the toxicity of the 309 ToxCast™ Phase I chemicals was assessed using a zebrafish screen for developmental toxicity. All exposures were by immersion from 6-8 h post fertilization (hpf) to 5 days post fertilization (dpf); nominal concentration range of 1 nM-80 μM. On 6 dpf larvae were assessed for death and overt structural defects. Results revealed that the majority (62%) of chemicals were toxic to the developing zebrafish; both toxicity incidence and potency was correlated with chemical class and hydrophobicity (logP); and inter-and intra-plate replicates showed good agreement. The zebrafish embryo screen, by providing an integrated model of the developing vertebrate, compliments the ToxCast assay portfolio and has the potential to provide information relative to overt and organismal toxicity.

Endocrine Profiling and Prioritization of Environmental Chemicals Using ToxCast Data

Background The prioritization of chemicals for toxicity testing is a primary goal of the U.S. Environmental Protection Agency (EPA) ToxCast™ program. Phase I of ToxCast used a battery of 467 in vitro, high-throughput screening assays to assess 309 environmental chemicals. One important mode of action leading to toxicity is endocrine disruption, and the U.S. EPA’s Endocrine Disruptor Screening Program (EDSP) has been charged with screening pesticide chemicals and environmental contaminants for their potential to affect the endocrine systems of humans and wildlife. Objective The goal of this study was to develop a flexible method to facilitate the rational prioritization of chemicals for further evaluation and demonstrate its application as a candidate decision-support tool for EDSP. Methods Focusing on estrogen, androgen, and thyroid pathways, we defined putative endocrine profiles and derived a relative rank or score for the entire ToxCast library of 309 unique chemicals. Effects on other nuclear receptors and xenobiotic metabolizing enzymes were also considered, as were pertinent chemical descriptors and pathways relevant to endocrine-mediated signaling. Results Combining multiple data sources into an overall, weight-of-evidence Toxicological Priority Index (ToxPi) score for prioritizing further chemical testing resulted in more robust conclusions than any single data source taken alone. Conclusions Incorporating data from in vitro assays, chemical descriptors, and biological pathways in this prioritization schema provided a flexible, comprehensive visualization and ranking of each chemical’s potential endocrine activity. Importantly, ToxPi profiles provide a transparent visualization of the relative contribution of all information sources to an overall priority ranking. The method developed here is readily adaptable to diverse chemical prioritization tasks.

Zebrafish: as an integrative model for twenty-first century toxicity testing.

The zebrafish embryo is a useful small model for investigating vertebrate development because of its transparency, low cost, transgenic and morpholino capabilities, conservation of cell signaling, and concordance with mammalian developmental phenotypes. From these advantages, the zebrafish embryo has been considered as an alternative model for traditional in vivo developmental toxicity screening. The use of this organism in conjunction with traditional in vivo developmental toxicity testing has the potential to reduce cost and increase throughput of testing the chemical universe, prioritize chemicals for targeted toxicity testing, generate predictive models of developmental toxicants, and elucidate mechanisms and adverse outcome pathways for abnormal development. This review gives an overview of the zebrafish embryo for pre dictive toxicology and 21st century toxicity testing. Developmental eye defects were selected as an example to evaluate data from the U.S. Environmental Protection Agencys ToxCast program comparing responses in zebrafish embryos with those from pregnant rats and rabbits for a subset of 24 environmental chemicals across >600 in vitro assay targets. Cross-species comparisons implied a common basis for biological pathways associated with neuronal defects, extracellular matrix remodeling, and mitotic arrest.

Estimating toxicity-related biological pathway altering doses for high-throughput chemical risk assessment.

We describe a framework for estimating the human dose at which a chemical significantly alters a biological pathway in vivo, making use of in vitro assay data and an in vitro-derived pharmacokinetic model, coupled with estimates of population variability and uncertainty. The quantity we calculate, the biological pathway altering dose (BPAD), is analogous to current risk assessment metrics in that it combines dose-response data with analysis of uncertainty and population variability to arrive at conservative exposure limits. The analogy is closest when perturbation of a pathway is a key event in the mode of action (MOA) leading to a specified adverse outcome. Because BPADs are derived from relatively inexpensive, high-throughput screening (HTS) in vitro data, this approach can be applied to high-throughput risk assessments (HTRA) for thousands of data-poor environmental chemicals. We envisage the first step of HTRA to be an assessment of in vitro concentration-response relationships across biologically important pathways to derive biological pathway altering concentrations (BPAC). Pharmacokinetic (PK) modeling is then used to estimate the in vivo doses required to achieve the BPACs in the blood at steady state. Uncertainty and variability are incorporated in both the BPAC and the PK parameters and then combined to yield a probability distribution for the dose required to perturb the critical pathway. We finally define the BPADL as the lower confidence bound of this pathway-altering dose. This perspective outlines a framework for using HTRA to estimate BPAD values; provides examples of the use of this approach, including a comparison of BPAD values with published dose-response data from in vivo studies; and discusses challenges and alternative formulations.

Predictive Models of Prenatal Developmental Toxicity from ToxCast High-Throughput Screening Data

Environmental Protection Agencys ToxCast project is profiling the in vitro bioactivity of chemicals to assess pathway-level and cell-based signatures that correlate with observed in vivo toxicity. We hypothesized that developmental toxicity in guideline animal studies captured in the ToxRefDB database would correlate with cell-based and cell-free in vitro high-throughput screening (HTS) data to reveal meaningful mechanistic relationships and provide models identifying chemicals with the potential to cause developmental toxicity. To test this hypothesis, we built statistical associations based on HTS and in vivo developmental toxicity data from ToxRefDB. Univariate associations were used to filter HTS assays based on statistical correlation with distinct in vivo endpoint. This revealed 423 total associations with distinctly different patterns for rat (301 associations) and rabbit (122 associations) across multiple HTS assay platforms. From these associations, linear discriminant analysis with cross-validation was used to build the models. Species-specific models of predicted developmental toxicity revealed strong balanced accuracy (> 70%) and unique correlations between assay targets such as transforming growth factor beta, retinoic acid receptor, and G-protein-coupled receptor signaling in the rat and inflammatory signals, such as interleukins (IL) (IL1a and IL8) and chemokines (CCL2), in the rabbit. Species-specific toxicity endpoints were associated with one another through common Gene Ontology biological processes, such as cleft palate to urogenital defects through placenta and embryonic development. This work indicates the utility of HTS assays for developing pathway-level models predictive of developmental toxicity.

Analysis of Eight Oil Spill Dispersants Using Rapid, In Vitro Tests for Endocrine and Other Biological Activity

The Deepwater Horizon oil spill has led to the use of >1 M gallons of oil spill dispersants, which are mixtures of surfactants and solvents. Because of this large scale use there is a critical need to understand the potential for toxicity of the currently used dispersant and potential alternatives, especially given the limited toxicity testing information that is available. In particular, some dispersants contain nonylphenol ethoxylates (NPEs), which can degrade to nonylphenol (NP), a known endocrine disruptor. Given the urgent need to generate toxicity data, we carried out a series of in vitro high-throughput assays on eight commercial dispersants. These assays focused on the estrogen and androgen receptors (ER and AR), but also included a larger battery of assays probing other biological pathways. Cytotoxicity in mammalian cells was also quantified. No activity was seen in any AR assay. Two dispersants showed a weak ER signal in one assay (EC50 of 16 ppm for Nokomis 3-F4 and 25 ppm for ZI-400). NPs and NPEs also had a weak signal in this same ER assay. Note that Corexit 9500, the currently used product, does not contain NPEs and did not show any ER activity. Cytotoxicity values for six of the dispersants were statistically indistinguishable, with median LC50 values approximately 100 ppm. Two dispersants, JD 2000 and SAF-RON GOLD, were significantly less cytotoxic than the others with LC50 values approaching or exceeding 1000 ppm.

High-throughput models for exposure-based chemical prioritization in the ExpoCast project.

The United States Environmental Protection Agency (U.S. EPA) must characterize potential risks to human health and the environment associated with manufacture and use of thousands of chemicals. High-throughput screening (HTS) for biological activity allows the ToxCast research program to prioritize chemical inventories for potential hazard. Similar capabilities for estimating exposure potential would support rapid risk-based prioritization for chemicals with limited information; here, we propose a framework for high-throughput exposure assessment. To demonstrate application, an analysis was conducted that predicts human exposure potential for chemicals and estimates uncertainty in these predictions by comparison to biomonitoring data. We evaluated 1936 chemicals using far-field mass balance human exposure models (USEtox and RAIDAR) and an indicator for indoor and/or consumer use. These predictions were compared to exposures inferred by Bayesian analysis from urine concentrations for 82 chemicals reported in the National Health and Nutrition Examination Survey (NHANES). Joint regression on all factors provided a calibrated consensus prediction, the variance of which serves as an empirical determination of uncertainty for prioritization on absolute exposure potential. Information on use was found to be most predictive; generally, chemicals above the limit of detection in NHANES had consumer/indoor use. Coupled with hazard HTS, exposure HTS can place risk earlier in decision processes. High-priority chemicals become targets for further data collection.