Non-invasive in vitro NAM for the detection of reversible and irreversible eye damage after chemical exposure for GHS classification purposes (ImAi).

The potential risk of chemicals to the human eye is assessed by adopted test guidelines (TGs) for regulatory purposes to ensure consumer safety. Over the past decade, the Organization for Economic Co-operation and Development (OECD) has approved new approach methodologies (NAMs) to predict chemical eye damage. However, existing NAMs remain associated with limitations: First, no full replacement of the in vivo Draize eye test due to limited predictability of severe/mild damage was reached.

In-situ electrochemical impedance analysis of a commercial SOFC stack fueled by real wood gas.

The combination of solid oxide fuel cells (SOFCs) and wood gasification has the potential to significantly increase renewable electricity production and decrease emissions. Depending on the quality of the wood gas, degradation processes have a significant impact on the reliability and lifetime of the SOFC. Using electrochemical impedance spectroscopy (EIS) and subsequent distribution of relaxation times (DRT) analysis, the impact on the degradation of coupling wood gasification with a commercial SOFC stack is determined in this study.

Next generation risk assessment for occupational chemical safety - A real world example with sodium-2-hydroxyethane sulfonate.

Next Generation Risk Assessment (NGRA) is an exposure-led approach to safety assessment that uses New Approach Methodologies (NAMs). Application of NGRA has been largely restricted to assessments of consumer use of cosmetics and is not currently implemented in occupational safety assessments, e.g.

Advancing probabilistic risk assessment by integrating human biomonitoring, new approach methods, and Bayesian modeling: A case study with the mycotoxin deoxynivalenol.

Deoxynivalenol (DON) is a mycotoxin frequently observed in cereals and cereal-based foods, with reported toxicological effects including reduced body weight, immunotoxicity and reproductive defects. The European Food Safety Authority used traditional risk assessment approaches to derive a deterministic Tolerable Daily Intake (TDI) of 1 μg/kg-day, however data from human biomarkers studies indicate widespread and variable exposure worldwide, necessitating more sophisticated and advanced methods to quantify population risk. The World Health Organization/International Programme on Chemical Safety (WHO/IPCS) has previously used DON as a case example in replacing the TDI with a probabilistic toxicity value, using default uncertainty and variability distributions to derive the Human Dose corresponding to an effect size M in the I percentile of the population (HD) for M = 5 % decrease in body weight and I = 1 %.

Integrative Chemical-Biological Grouping of Complex High Production Volume Substances from Lower Olefin Manufacturing Streams.

Human cell-based test methods can be used to evaluate potential hazards of mixtures and products of petroleum refining ("unknown or variable composition, complex reaction products, or biological materials" substances, UVCBs). Analyses of bioactivity and detailed chemical characterization of petroleum UVCBs were used separately for grouping these substances; a combination of the approaches has not been undertaken. Therefore, we used a case example of representative high production volume categories of petroleum UVCBs, 25 lower olefin substances from low benzene naphtha and resin oils categories, to determine whether existing manufacturing-based category grouping can be supported.

An interdisciplinary framework for derivation of occupational exposure limits.

Protecting the health and safety of workers in industrial operations is a top priority. One of the resources used in industry to ensure worker safety is the occupational exposure limit (OEL). OELs are derived from the assessment and interpretation of empirical data from animal and/or human studies.

Grouping of UVCB substances with dose-response transcriptomics data from human cell-based assays.

The application of in vitro biological assays as new approach methodologies (NAMs) to support grouping of UVCB (unknown or variable composition, complex reaction products, and biological materials) substances has recently been demonstrated. In addition to cell-based phenotyping as NAMs, in vitro transcriptomic profiling is used to gain deeper mechanistic understanding of biological responses to chemicals and to support grouping and read-across. However, the value of gene expression profiling for characterizing complex substances like UVCBs has not been explored.

Utilizing ion mobility spectrometry-mass spectrometry for the characterization and detection of persistent organic pollutants and their metabolites.

Persistent organic pollutants (POPs) are xenobiotic chemicals of global concern due to their long-range transport capabilities, persistence, ability to bioaccumulate, and potential to have negative effects on human health and the environment. Identifying POPs in both the environment and human body is therefore essential for assessing potential health risks, but their diverse range of chemical classes challenge analytical techniques. Currently, platforms coupling chromatography approaches with mass spectrometry (MS) are the most common analytical methods employed to evaluate both parent POPs and their respective metabolites and/or degradants in samples ranging from d rinking water to biofluids.

Revealing Adverse Outcome Pathways from Public High-Throughput Screening Data to Evaluate New Toxicants by a Knowledge-Based Deep Neural Network Approach.

Traditional experimental testing to identify endocrine disruptors that enhance estrogenic signaling relies on expensive and labor-intensive experiments. We sought to design a knowledge-based deep neural network (k-DNN) approach to reveal and organize public high-throughput screening data for compounds with nuclear estrogen receptor α and β (ERα and ERβ) binding potentials. The target activity was rodent uterotrophic bioactivity driven by ERα/ERβ activations.

Grouping of UVCB substances with new approach methodologies (NAMs) data.

One of the most challenging areas in regulatory science is assessment of the substances known as UVCB (unknown or variable composition, complex reaction products and biological materials). Because the inherent complexity and variability of UVCBs present considerable challenges for establishing sufficient substance similarity based on chemical characteristics or other data, we hypothesized that new approach methodologies (NAMs), including in vitro test-derived biological activity signatures to characterize substance similarity, could be used to support grouping of UVCBs. We tested 141 petroleum substances as representative UVCBs in a compendium of 15 human cell types representing a variety of tissues.

Predictive modeling of estrogen receptor agonism, antagonism, and binding activities using machine- and deep-learning approaches.

As defined by the World Health Organization, an endocrine disruptor is an exogenous substance or mixture that alters function(s) of the endocrine system and consequently causes adverse health effects in an intact organism, its progeny, or (sub)populations. Traditional experimental testing regimens to identify toxicants that induce endocrine disruption can be expensive and time-consuming. Computational modeling has emerged as a promising and cost-effective alternative method for screening and prioritizing potentially endocrine-active compounds.

Cardiovascular Effects of Polychlorinated Biphenyls and Their Major Metabolites.

Background: Xenobiotic metabolism is complex, and accounting for bioactivation and detoxification processes of chemicals remains among the most challenging aspects for decision making with new approach methods data.

Objectives: Considering the physiological relevance of human organotypic culture models and their utility for high-throughput screening, we hypothesized that multidimensional chemical-biological profiling of chemicals and their major metabolites is a sensible alternative for the toxicological characterization of parent molecules vs. metabolites .

Population-based toxicity screening in human induced pluripotent stem cell-derived cardiomyocytes.

The potential for cardiotoxicity is carefully evaluated for pharmaceuticals, as it is a major safety liability. However, environmental chemicals are seldom tested for their cardiotoxic potential. Moreover, there is a large variability in both baseline and drug-induced cardiovascular risk in humans, but data are lacking on the degree to which susceptibility to chemically-induced cardiotoxicity may also vary.

Optimal Chemical Grouping and Sorbent Material Design by Data Analysis, Modeling and Dimensionality Reduction Techniques.

The ultimate goal of the Texas A&M Superfund program is to develop comprehensive tools and models for addressing exposure to chemical mixtures during environmental emergency-related contamination events. With that goal, we aim to design a framework for optimal grouping of chemical mixtures based on their chemical characteristics and bioactivity properties, and facilitate comparative assessment of their human health impacts through read-across. The optimal clustering of the chemical mixtures guides the selection of sorption material in such a way that the adverse health effects of each group are mitigated.

Multi-dimensional in vitro bioactivity profiling for grouping of glycol ethers.

High-content screening data derived from physiologically-relevant in vitro models promise to improve confidence in data-integrative groupings for read-across in human health safety assessments. The biological data-based read-across concept is especially applicable to bioactive chemicals with defined mechanisms of toxicity; however, the challenge of data-derived groupings for chemicals that are associated with little or no bioactivity has not been explored. In this study, we apply a suite of organotypic and population-based in vitro models for comprehensive bioactivity profiling of twenty E-Series and P-Series glycol ethers, solvents with a broad variation in toxicity ranging from relatively non-toxic to reproductive and hematopoetic system toxicants.

Thorough QT/QTc in a Dish: An In Vitro Human Model That Accurately Predicts Clinical Concentration-QTc Relationships.

"Thorough QT/corrected QT (QTc)" (TQT) studies are cornerstones of clinical cardiovascular safety assessment. However, TQT studies are resource intensive, and preclinical models predictive of the threshold of regulatory concern are lacking. We hypothesized that an in vitro model using induced pluripotent stem cell (iPSC)-derived cardiomyocytes from a diverse sample of human subjects can serve as a "TQT study in a dish.

Technology Transfer of the Microphysiological Systems: A Case Study of the Human Proximal Tubule Tissue Chip.

The adoption of a new technology into basic research, and industrial and clinical settings requires rigorous testing to build confidence in the reproducibility, reliability, robustness, and relevance of these models. Tissue chips are promising new technology, they have the potential to serve as a valuable tool in biomedical research, as well as pharmaceutical development with regards to testing for efficacy and safety. The principal goals of this study were to validate a previously established proximal tubule tissue chip model in an independent laboratory and to extend its utility to testing of nephrotoxic compounds.

A human population-based organotypic in vitro model for cardiotoxicity screening.

Assessing inter-individual variability in responses to xenobiotics remains a substantial challenge, both in drug development with respect to pharmaceuticals and in public health with respect to environmental chemicals. Although approaches exist to characterize pharmacokinetic variability, there are no methods to routinely address pharmacodynamic variability. In this study, we aimed to demonstrate the feasibility of characterizing inter-individual variability in a human in vitro model.

ToxPi Graphical User Interface 2.0: Dynamic exploration, visualization, and sharing of integrated data models.

Background: Drawing integrated conclusions from diverse source data requires synthesis across multiple types of information. The ToxPi (Toxicological Prioritization Index) is an analytical framework that was developed to enable integration of multiple sources of evidence by transforming data into integrated, visual profiles. Methodological improvements have advanced ToxPi and expanded its applicability, necessitating a new, consolidated software platform to provide functionality, while preserving flexibility for future updates.

High-Content Assay Multiplexing for Vascular Toxicity Screening in Induced Pluripotent Stem Cell-Derived Endothelial Cells and Human Umbilical Vein Endothelial Cells.

Endothelial cells (ECs) play a major role in blood vessel formation and function. While there is longstanding evidence for the potential of chemical exposures to adversely affect EC function and vascular development, the hazard potential of chemicals with respect to vascular effects is not routinely evaluated in safety assessments. Induced pluripotent stem cell (iPSC)-derived ECs promise to provide a physiologically relevant, organotypic culture model that is amenable for high-throughput (HT) EC toxicant screening and may represent a viable alternative to traditional in vitro models, including human umbilical vein endothelial cells (HUVECs).

Grouping of Petroleum Substances as Example UVCBs by Ion Mobility-Mass Spectrometry to Enable Chemical Composition-Based Read-Across.

Substances of Unknown or Variable composition, Complex reaction products, and Biological materials (UVCBs), including many refined petroleum products, present a major challenge in regulatory submissions under the EU Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH) and US High Production Volume regulatory regimes. The inherent complexity of these substances, as well as variability in composition obfuscates detailed chemical characterization of each individual substance and their grouping for human and environmental health evaluation through read-across. In this study, we applied ion mobility mass spectrometry in conjunction with cheminformatics-based data integration and visualization to derive substance-specific signatures based on the distribution and abundance of various heteroatom classes.

In vitro cardiotoxicity assessment of environmental chemicals using an organotypic human induced pluripotent stem cell-derived model.

An important target area for addressing data gaps through in vitro screening is the detection of potential cardiotoxicants. Despite the fact that current conservative estimates relate at least 23% of all cardiovascular disease cases to environmental exposures, the identities of the causative agents remain largely uncharacterized. Here, we evaluate the feasibility of a combinatorial in vitro/in silico screening approach for functional and mechanistic cardiotoxicity profiling of environmental hazards using a library of 69 representative environmental chemicals and drugs.

A chemical-biological similarity-based grouping of complex substances as a prototype approach for evaluating chemical alternatives.

Comparative assessment of potential human health impacts is a critical step in evaluating both chemical alternatives and existing products on the market. Most alternatives assessments are conducted on a chemical-by-chemical basis and it is seldom acknowledged that humans are exposed to complex products, not individual substances. Indeed, substances of nknown or ariable composition, omplex reaction products, and iological materials (UVCBs) are ubiquitous in commerce yet they present a major challenge for registration and health assessments.