Chemistry domain of applicability evaluation against existing estrogen receptor high-throughput assay-based activity models.

Introduction: The U. S. Environmental Protection Agency's Endocrine Disruptor Screening Program (EDSP) Tier 1 assays are used to screen for potential endocrine system-disrupting chemicals.

Smoking cessation, harm reduction, and biomarkers protocols in the PhenX Toolkit: Tools for standardized data collection.

The use of standard protocols in studies supports consistent data collection, improves data quality, and facilitates cross-study analyses. Funded by the National Institutes of Health, the PhenX (consensus measures for otypes and eposures) Toolkit is a catalog of recommended measurement protocols that address a wide range of research topics and are suitable for inclusion in a variety of study designs. In 2020, a PhenX Working Group of smoking cessation experts followed a well-established consensus process to identify and recommend measurement protocols suitable for inclusion in smoking cessation and smoking harm reduction studies.

Optimizing androgen receptor prioritization using high-throughput assay-based activity models.

Computational models using data from high-throughput screening assays have promise for prioritizing and screening chemicals for testing under the U.S. Environmental Protection Agency's Endocrine Disruptor Screening Program (EDSP).

Evaluating the utility of the Threshold of Toxicological Concern (TTC) and its exclusions in the biocompatibility assessment of extractable chemical substances from medical devices.

The Threshold of Toxicological Concern (TTC) is a pragmatic approach used to establish safe thresholds below which there can be no appreciable risk to human health. Here, a large inventory of ~45,000 substances (referred to as the LRI dataset) was profiled through the Kroes TTC decision module within Toxtree v3.1 to assign substances into their respective TTC categories.

Linking complex disease and exposure data-insights from an environmental and occupational health study.

The disparate measurement protocols used to collect study data are an intrinsic barrier to combining information from environmental health studies. Using standardized measurement protocols and data standards for environmental exposures addresses this gap by improving data collection quality and consistency. To assess the prevalence of environmental exposures in National Institutes of Health (NIH) public data repositories and resources and to assess the commonality of the data elements, we analyzed clinical measures and exposure assays by comparing the Caribbean Consortium for Research in Environmental and Occupational Health study with selected NIH environmental health resources and studies.

Mapping Mechanistic Pathways of Acute Oral Systemic Toxicity Using Chemical Structure and Bioactivity Measurements.

Regulatory agencies around the world have committed to reducing or eliminating animal testing for establishing chemical safety. Adverse outcome pathways can facilitate replacement by providing a mechanistic framework for identifying the appropriate non-animal methods and connecting them to apical adverse outcomes. This study separated 11,992 chemicals with curated rat oral acute toxicity information into clusters of structurally similar compounds.

An evaluation of the performance of selected (Q)SARs/expert systems for predicting acute oral toxicity.

Multiple US agencies use acute oral toxicity data in a variety of regulatory contexts. One of the ad-hoc groups that the US Interagency Coordinating Committee on the Validation of Alternative Methods (ICCVAM) established to implement the ICCVAM Strategic Roadmap was the Acute Toxicity Workgroup (ATWG) to support the development, acceptance, and actualisation of new approach methodologies (NAMs). One of the ATWG charges was to evaluate and methods for predicting rat acute systemic toxicity.

Derivation of New Threshold of Toxicological Concern Values for Exposure via Inhalation for Environmentally-Relevant Chemicals.

The requirements of amended Toxic Substances Control Act (TSCA) stipulates that the US Environmental Protection Agency (US EPA) evaluate existing chemicals and make risk based assessments. There are ~33,000 substances that are active in commerce on the TSCA public non-confidential inventory, many of which lack available toxicity and exposure information to inform risk-based decision making. One approach to facilitate the assessment of these substances being considered is the Threshold of Toxicological Concern (TTC).

Identification of novel activators of the metal responsive transcription factor (MTF-1) using a gene expression biomarker in a microarray compendium.

Environmental exposure to metals is known to cause a number of human toxicities including cancer. Metal-responsive transcription factor 1 (MTF-1) is an important component of metal regulation systems in mammalian cells. Here, we describe a novel method to identify chemicals that activate MTF-1 based on microarray profiling data.

In Silico Guidance for In Vitro Androgen and Glucocorticoid Receptor ToxCast Assays.

Molecular initiating events (MIEs) are key events in adverse outcome pathways that link molecular chemistry to target biology. As they are based on chemistry, these interactions are excellent targets for computational chemistry approaches to in silico modeling. In this work, we aim to link ligand chemical structures to MIEs for androgen receptor (AR) and glucocorticoid receptor (GR) binding using ToxCast data.

Comparing and contrasting the coverage of publicly available structural alerts for protein binding.

The molecular initiating event for many mechanisms of toxicological action comprise the reactive, covalent binding between an exogenous electrophile and an endogenous nucleophile. The target sites for electrophiles are typically peptides, proteins, enzymes or DNA. Of these, the formation of covalent adducts with proteins and DNA are perhaps the most established as they are most closely associated with skin sensitisation and genotoxicity endpoints.

Evaluating potential refinements to existing Threshold of Toxicological Concern (TTC) values for environmentally-relevant compounds.

The Toxic Substances Control Act (TSCA) mandates the US EPA perform risk-based prioritisation of chemicals in commerce and then, for high-priority substances, develop risk evaluations that integrate toxicity data with exposure information. One approach being considered for data poor chemicals is the Threshold of Toxicological Concern (TTC). Here, TTC values derived using oral (sub)chronic No Observable (Adverse) Effect Level (NO(A)EL) data from the EPA's Toxicity Values database (ToxValDB) were compared with published TTC values from Munro et al.

A weight of evidence approach to investigate potential common mechanisms in pesticide groups to support cumulative risk assessment: A case study with dinitroaniline pesticides.

In 2016, the United States Environmental Protection Agency's (EPA) Office of Pesticide Programs published guidelines for establishing candidate common mechanism groups (CMGs) for cumulative risk assessment (CRA) weight-of-evidence-based screenings. A candidate CMG is a group of chemicals that may share similar structure, apical endpoints, and/or mechanistic data that suggest the potential for a common mechanism of toxicity among them. Here, a weight-of-evidence approach is presented to establish candidacy of a CMG for a group of nine dinitroaniline pesticides.

A Mechanistic Framework for Integrating Chemical Structure and High-Throughput Screening Results to Improve Toxicity Predictions.

Adverse Outcome Pathways (AOPs) establish a connection between a molecular initiating event (MIE) and an adverse outcome. Detailed understanding of the MIE provides the ideal data for determining chemical properties required to elicit the MIE. This study utilized high-throughput screening data from the ToxCast program, coupled with chemical structural information, to generate chemical clusters using three similarity methods pertaining to nine MIEs within an AOP network for hepatic steatosis.

Differentiating Pathway-Specific From Nonspecific Effects in High-Throughput Toxicity Data: A Foundation for Prioritizing Adverse Outcome Pathway Development.

The U.S. Environmental Protection Agency's ToxCast program has screened thousands of chemicals for biological activity, primarily using high-throughput in vitro bioassays.

Editor's Highlight: Negative Predictors of Carcinogenicity for Environmental Chemicals.

Recent international efforts have led to proposals for modified carcinogenicity testing paradigms based on data from shorter-term studies. The main goal of the current study was to evaluate the negative predictive value (NPV) of short-term toxicity indicators on carcinogenicity study outcomes and cancer classifications for chemicals previously reviewed by the U.S.

Accelerating Adverse Outcome Pathway Development Using Publicly Available Data Sources.

The adverse outcome pathway (AOP) concept links molecular perturbations with organism and population-level outcomes to support high-throughput toxicity (HTT) testing. International efforts are underway to define AOPs and store the information supporting these AOPs in a central knowledge base; however, this process is currently labor-intensive and time-consuming. Publicly available data sources provide a wealth of information that could be used to define computationally predicted AOPs (cpAOPs), which could serve as a basis for creating expert-derived AOPs in a much more efficient way.

Development of an in Silico Profiler for Mitochondrial Toxicity.

This study outlines the analysis of mitochondrial toxicity for a variety of pharmaceutical drugs extracted from Zhang et al. ((2009) Toxicol. In Vitro, 23, 134-140).

Methods for assigning confidence to toxicity data with multiple values--Identifying experimental outliers.

The assessment of data quality is a crucial element in many disciplines such as predictive toxicology and risk assessment. Currently, the reliability of toxicity data is assessed on the basis of testing information alone (adherence to Good Laboratory Practice (GLP), detailed testing protocols, etc.).