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

Recommendations on fit-for-purpose criteria to establish quality management for microphysiological systems and for monitoring their reproducibility

Cell culture technology has evolved, moving from single-cell and monolayer methods to 3D models like reaggregates, spheroids, and organoids, improved with bioengineering like microfabrication and bioprinting. These advancements, termed microphysiological systems (MPSs), closely replicate tissue environments and human physiology, enhancing research and biomedical uses. However, MPS complexity introduces standardization challenges, impacting reproducibility and trust. We offer guidelines for quality management and control criteria specific to MPSs, facilitating reliable outcomes without stifling innovation. Our fit-for-purpose recommendations provide actionable advice for achieving consistent MPS performance.

Towards systematic read-across using Generalised Read-Across (GenRA)

Read-across continues to be a popular data gap filling technique within category and analogue approaches. One of the main issues hindering read-across acceptance is the notion of addressing and reducing uncertainties. Frameworks and formats have been created to help facilitate read-across development, evaluation, and residual uncertainties. However, read-across remains an expert-driven approach with each assessment decided on its own merits with no objective means of evaluating performance or quantifying uncertainties. Here, the underlying motivation of creating an algorithmic approach to read-across, namely the Generalised Read-Across (GenRA) approach, is described. The overall objectives of the approach were to quantify performance and uncertainty. Progress made in quantifying the impact of each similarity context commonly relied upon as part of read-across assessment are discussed. The framework underpinning the approach, the software tools developed to date and how GenRA can be used to make and interpret predictions as part of a screening level hazard assessment decision context are illustrated. Future directions and some of the overarching issues still needed in this field and the extent to which GenRA might facilitate those needs are discussed.

A scheme to evaluate structural alerts to predict toxicity - Assessing confidence by characterising uncertainties

Structure-activity relationships (SARs) in toxicology have enabled the formation of structural rules which, when coded as structural alerts, are essential tools in in silico toxicology. Whilst other in silico methods have approaches for their evaluation, there is no formal process to assess the confidence that may be associated with a structural alert. This investigation proposes twelve criteria to assess the uncertainty associated with structural alerts, allowing for an assessment of confidence. The criteria are based around the stated purpose, description of the chemistry, toxicology and mechanism, performance and coverage, as well as corroborating and supporting evidence of the alert. Alerts can be given a confidence assessment and score, enabling the identification of areas where more information may be beneficial. The scheme to evaluate structural alerts was placed in the context of various use cases for industrial and regulatory applications. The analysis of alerts, and consideration of the evaluation scheme, identifies the different characteristics an alert may have, such as being highly specific or generic. These characteristics may determine when an alert can be used for specific uses such as identification of analogues for read-across or hazard identification.

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Structural alerts are useful tools for predictive toxicology.

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12 criteria to evaluate structural alerts have been identified.

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A strategy to determine confidence of structural alerts is presented.

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Different use cases require different characteristics of structural alerts.

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A Scheme to Evaluate Structural Alerts to Predict Toxicity – Assessing Confidence By Characterising Uncertainties.

Variability in in vivo studies: Defining the upper limit of performance for predictions of systemic effect levels

New approach methodologies (NAMs) for chemical hazard assessment are often evaluated via comparison to animal studies; however, variability in animal study data limits NAM accuracy. The US EPA Toxicity Reference Database (ToxRefDB) enables consideration of variability in effect levels, including the lowest effect level (LEL) for a treatment-related effect and the lowest observable adverse effect level (LOAEL) defined by expert review, from subacute, subchronic, chronic, multi-generation reproductive, and developmental toxicity studies. The objectives of this work were to quantify the variance within systemic LEL and LOAEL values, defined as potency values for effects in adult or parental animals only, and to estimate the upper limit of NAM prediction accuracy. Multiple linear regression (MLR) and augmented cell means (ACM) models were used to quantify the total variance, and the fraction of variance in systemic LEL and LOAEL values explained by available study descriptors (e.g., administration route, study type). The MLR approach considered each study descriptor as an independent contributor to variance, whereas the ACM approach combined categorical descriptors into cells to define replicates. Using these approaches, total variance in systemic LEL and LOAEL values (in log10-mg/kg/day units) ranged from 0.74 to 0.92. Unexplained variance in LEL and LOAEL values, approximated by the residual mean square error (MSE), ranged from 0.20-0.39. Considering subchronic, chronic, or developmental study designs separately resulted in similar values. Based on the relationship between MSE and R-squared for goodness-of-fit, the maximal R-squared may approach 55 to 73% for a NAM-based predictive model of systemic toxicity using these data as reference. The root mean square error (RMSE) ranged from 0.47 to 0.63 log10-mg/kg/day, depending on dataset and regression approach, suggesting that a two-sided minimum prediction interval for systemic effect levels may have a width of 58 to 284-fold. These findings suggest quantitative considerations for building scientific confidence in NAM-based systemic toxicity predictions.

Development of a prioritization method for chemical-mediated effects on steroidogenesis using an integrated statistical analysis of high-throughput H295R data

Synthesis of 11 steroid hormones in human adrenocortical carcinoma cells (H295R) was measured in a high-throughput steroidogenesis assay (HT-H295R) for 656 chemicals in concentration-response as part of the US Environmental Protection Agency's ToxCast program. This work extends previous analysis of the HT-H295R dataset and model by examining the utility of a novel prioritization metric based on the Mahalanobis distance that reduced these 11-dimensional data to 1-dimension via calculation of a mean Mahalanobis distance (mMd) at each chemical concentration screened for all hormone measures available. Herein, we evaluated the robustness of mMd values, and demonstrate that covariance and variance of the hormones measured appear independent of the chemicals screened and are inherent to the assay; the Type I error rate of the mMd method is less than 1%; and, absolute fold changes (up or down) of 1.5 to 2-fold have sufficient power for statistical significance. As a case study, we examined hormone responses for aromatase inhibitors in the HT-H295R assay and found high concordance with other ToxCast assays for known aromatase inhibitors. Finally, we used mMd and other ToxCast cytotoxicity data to demonstrate prioritization of the most selective and active chemicals as candidates for further in vitro or in silico screening.

An Adverse Outcome Pathway (AOP) for forestomach tumors induced by non-genotoxic initiating events

The utility of rodent forestomach tumor data for hazard and risk assessment has been examined for decades because humans do not have a forestomach, and these tumors occur by varying modes of action (MOAs). We have used the MOA for ethyl acrylate (EA) to develop an Adverse Outcome Pathway (AOP) for forestomach tumors caused by non-genotoxic initiating events. These tumors occur secondary to site of contact induced epithelial cytotoxicity and regenerative repair-driven proliferation. For EA, the critical initiating event (IE) is epithelial cytotoxicity, and supporting key events (KEs) at the cellular and tissue level are increased cell proliferation (KE1) resulting in sustained hyperplasia (KE2), with the adverse outcome of forestomach papillomas and carcinomas. For EA, a pre-molecular initiating event (pre-MIE) of sustained glutathione depletion is probable. Supporting data from butylated hydroxyanisole (BHA) are also reviewed. Although there may be some variability in the pre-MIEs and IEs for BHA and EA, they share the same KEs, and evidence for BHA confers support for the AOP. Evolved Bradford Hill considerations of biological plausibility, essentiality, and empirical support were evaluated per OECD guidance. Although an MIE is not specifically described, overall confidence in the AOP is high due to well-developed and accepted evidence streams, and the AOP can be used for regulatory applications including hazard identification and risk assessment for chemicals that act by this AOP.

From the exposome to mechanistic understanding of chemical-induced adverse effects

The exposome encompasses an individual's exposure to exogenous chemicals, as well as endogenous chemicals that are produced or altered in response to external stressors. While the exposome concept has been established for human health, its principles can be extended to include broader ecological issues. The assessment of exposure is tightly interlinked with hazard assessment. Here, we explore if mechanistic understanding of the causal links between exposure and adverse effects on human health and the environment can be improved by integrating the exposome approach with the adverse outcome pathway (AOP) concept that structures and organizes the sequence of biological events from an initial molecular interaction of a chemical with a biological target to an adverse outcome. Complementing exposome research with the AOP concept may facilitate a mechanistic understanding of stress-induced adverse effects, examine the relative contributions from various components of the exposome, determine the primary risk drivers in complex mixtures, and promote an integrative assessment of chemical risks for both human and environmental health.

Activity of Zearalenone in the Porcine Intestinal Tract

This study demonstrates that low doses (somewhat above the No Observed Adverse Effect Level, NOAEL) of the mycoestrogen zearalenone (ZEN) and its metabolites display multispecificity towards various biological targets in gilts. The observed responses in gilts were surprising. The presence of ZEN and zearalenols (ZELs) did not evoke a response in the porcine gastrointestinal tract, which was attributed to dietary tolerance. Lymphocyte proliferation was intensified in jejunal mesenteric lymph nodes, and lymphocyte counts increased in the jejunal epithelium with time of exposure. In the distal digestive tract, fecal bacterial counts decreased, the activity of fecal bacterial enzymes and lactic acid bacteria increased, and cecal water was characterized by higher genotoxicity. The accompanying hyperestrogenism led to changes in mRNA activity of selected enzymes (cytochrome P450, hydroxysteroid dehydrogenases, nitric oxide synthases) and receptors (estrogen and progesterone receptors), and it stimulated post-translational modifications which play an important role in non-genomic mechanisms of signal transmission. Hyperestrogenism influences the regulation of the host's steroid hormones (estron, estradiol and progesteron), it affects the virulence of bacterial genes encoding bacterial hydroxysteroid dehydrogenases (HSDs), and it participates in detoxification processes by slowing down intestinal activity, provoking energy deficits and promoting antiporter activity at the level of enterocytes. In most cases, hyperestrogenism fulfils all of the above roles. The results of this study indicate that low doses of ZEN alleviate inflammatory processes in the digestive system, in particular in the proximal and distal intestinal tract, and increase body weight gains in gilts.

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 Unknown or Variable composition, Complex reaction products, and Biological materials (UVCBs) are ubiquitous in commerce yet they present a major challenge for registration and health assessments. Here, we present a comprehensive experimental and computational approach to categorize UVCBs according to global similarities in their bioactivity using a suite of in vitro models. We used petroleum substances, an important group of UVCBs which are grouped for regulatory approval and read-across primarily on physico-chemical properties and the manufacturing process, and only partially based on toxicity data, as a case study. We exposed induced pluripotent stem cell-derived cardiomyocytes and hepatocytes to DMSO-soluble extracts of 21 petroleum substances from five product groups. Concentration-response data from high-content imaging in cardiomyocytes and hepatocytes, as well as targeted high-throughput transcriptomic analysis of the hepatocytes, revealed distinct groups of petroleum substances. Data integration showed that bioactivity profiling affords clustering of petroleum substances in a manner similar to the manufacturing process-based categories. Moreover, we observed a high degree of correlation between bioactivity profiles and physico-chemical properties, as well as improved groupings when chemical and biological data were combined. Altogether, we demonstrate how novel in vitro screening approaches can be effectively utilized in combination with physico-chemical characteristics to group complex substances and enable read-across. This approach allows for rapid and scientifically-informed evaluation of health impacts of both existing substances and their chemical alternatives.

ToxCast Chemical Landscape: Paving the Road to 21st Century Toxicology

The U.S. Environmental Protection Agency's (EPA) ToxCast program is testing a large library of Agency-relevant chemicals using in vitro high-throughput screening (HTS) approaches to support the development of improved toxicity prediction models. Launched in 2007, Phase I of the program screened 310 chemicals, mostly pesticides, across hundreds of ToxCast assay end points. In Phase II, the ToxCast library was expanded to 1878 chemicals, culminating in the public release of screening data at the end of 2013. Subsequent expansion in Phase III has resulted in more than 3800 chemicals actively undergoing ToxCast screening, 96% of which are also being screened in the multi-Agency Tox21 project. The chemical library unpinning these efforts plays a central role in defining the scope and potential application of ToxCast HTS results. The history of the phased construction of EPA's ToxCast library is reviewed, followed by a survey of the library contents from several different vantage points. CAS Registry Numbers are used to assess ToxCast library coverage of important toxicity, regulatory, and exposure inventories. Structure-based representations of ToxCast chemicals are then used to compute physicochemical properties, substructural features, and structural alerts for toxicity and biotransformation. Cheminformatics approaches using these varied representations are applied to defining the boundaries of HTS testability, evaluating chemical diversity, and comparing the ToxCast library to potential target application inventories, such as used in EPA's Endocrine Disruption Screening Program (EDSP). Through several examples, the ToxCast chemical library is demonstrated to provide comprehensive coverage of the knowledge domains and target inventories of potential interest to EPA. Furthermore, the varied representations and approaches presented here define local chemistry domains potentially worthy of further investigation (e.g., not currently covered in the testing library or defined by toxicity "alerts") to strategically support data mining and predictive toxicology modeling moving forward.

Application of the TGx-28.65 transcriptomic biomarker to classify genotoxic and non-genotoxic chemicals in human TK6 cells in the presence of rat liver S9

In vitro transcriptional signatures that predict toxicities can facilitate chemical screening. We previously developed a transcriptomic biomarker (known as TGx-28.65) for classifying agents as genotoxic (DNA damaging) and non-genotoxic in human lymphoblastoid TK6 cells. Because TK6 cells do not express cytochrome P450s, we confirmed accurate classification by the biomarker in cells co-exposed to 1% 5,6 benzoflavone/phenobarbital-induced rat liver S9 for metabolic activation. However, chemicals may require different types of S9 for activation. Here we investigated the response of TK6 cells to higher percentages of Aroclor-, benzoflavone/phenobarbital-, or ethanol-induced rat liver S9 to expand TGx-28.65 biomarker applicability. Transcriptional profiles were derived 3 to 4 hr following a 4 hr co-exposure of TK6 cells to test chemicals and S9. Preliminary studies established that 10% Aroclor- and 5% ethanol-induced S9 alone did not induce the TGx-28.65 biomarker genes. Seven genotoxic and two non-genotoxic chemicals (and concurrent solvent and positive controls) were then tested with one of the S9s (selected based on cell survival and micronucleus induction). Relative survival and micronucleus frequency was assessed by flow cytometry in cells 20 hr post-exposure. Genotoxic/non-genotoxic chemicals were accurately classified using the different S9s. One technical replicate of cells co-treated with dexamethasone and 10% Aroclor-induced S9 was falsely classified as genotoxic, suggesting caution in using high S9 concentrations. Even low concentrations of genotoxic chemicals (those not causing cytotoxicity) were correctly classified, demonstrating that TGx-28.65 is a sensitive biomarker of genotoxicity. A meta-analysis of datasets from 13 chemicals supports that different S9s can be used in TK6 cells, without impairing classification using the TGx-28.65 biomarker.

Integrated Approaches to Testing and Assessment

In this chapter, we explain how Integrated Approaches to Testing and Assessment (IATA) offer a means of integrating and translating the data generated by toxicity testing methods, thereby serving as flexible and suitable tools for toxicological decision making in the twenty-first century. In addition to traditional in vitro and in vivo testing methods, IATA are increasingly incorporating newly developed in vitro systems and measurement technologies such as high throughput screening and high content imaging. Computational approaches are also being used in IATA development, both as a means of generating data (e.g. QSARs), interpreting data (bioinformatics and chemoinformatics), and as a means of integrating multiple sources of data (e.g. expert systems, bayesian models). Decision analytic methods derived from socioeconomic theory can also play a role in developing flexible and optimal IATA solutions. Some of the challenges involved in the development, validation and implementation of IATA are also discussed.

A shift in paradigm towards human biology-based systems for cholestatic-liver diseases

Cholestatic-liver diseases (CLDs) arise from diverse causes ranging from genetic factors to drug-induced cholestasis. The so-called diseases of civilization (obesity, diabetes, metabolic disorders, non-alcoholic liver disease, cardiovascular diseases, etc.) are intricately implicated in liver and gall bladder diseases. Although CLDs have been extensively studied, there seem to be important gaps in the understanding of human disease. Despite the fact that many animal models exist and substantial clinical data are available, translation of this knowledge towards therapy has been disappointingly limited. Recent advances in liver cell culture such as in vivo-like 3D cultivation of human primary hepatic cells, human induced pluripotent stem cell-derived hepatocytes; and cutting-edge analytical techniques such as 'omics' technologies and high-content screenings could play a decisive role in deeper mechanistic understanding of CLDs. This Topical Review proposes a roadmap to human biology-based research using omics technologies providing quantitative information on mechanisms in an adverse outcome/disease pathway framework. With modern sensitive tools, a shift in paradigm in human disease research seems timely and even inevitable to overcome species barriers in translation.

A human liver microphysiology platform for investigating physiology, drug safety, and disease models

This paper describes the development and characterization of a microphysiology platform for drug safety and efficacy in liver models of disease that includes a human, 3D, microfluidic, four-cell, sequentially layered, self-assembly liver model (SQL-SAL); fluorescent protein biosensors for mechanistic readouts; as well as a microphysiology system database (MPS-Db) to manage, analyze, and model data. The goal of our approach is to create the simplest design in terms of cells, matrix materials, and microfluidic device parameters that will support a physiologically relevant liver model that is robust and reproducible for at least 28 days for stand-alone liver studies and microfluidic integration with other organs-on-chips. The current SQL-SAL uses primary human hepatocytes along with human endothelial (EA.hy926), immune (U937) and stellate (LX-2) cells in physiological ratios and is viable for at least 28 days under continuous flow. Approximately, 20% of primary hepatocytes and/or stellate cells contain fluorescent protein biosensors (called sentinel cells) to measure apoptosis, reactive oxygen species (ROS) and/or cell location by high content analysis (HCA). In addition, drugs, drug metabolites, albumin, urea and lactate dehydrogenase (LDH) are monitored in the efflux media. Exposure to 180 μM troglitazone or 210 μM nimesulide produced acute toxicity within 2-4 days, whereas 28 μM troglitazone produced a gradual and much delayed toxic response over 21 days, concordant with known mechanisms of toxicity, while 600 µM caffeine had no effect. Immune-mediated toxicity was demonstrated with trovafloxacin with lipopolysaccharide (LPS), but not levofloxacin with LPS. The SQL-SAL exhibited early fibrotic activation in response to 30 nM methotrexate, indicated by increased stellate cell migration, expression of alpha-smooth muscle actin and collagen, type 1, alpha 2. Data collected from the in vitro model can be integrated into a database with access to related chemical, bioactivity, preclinical and clinical information uploaded from external databases for constructing predictive models.

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.

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.

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.

Applying Adverse Outcome Pathways (AOPs) to support Integrated Approaches to Testing and Assessment (IATA)

Chemical regulation is challenged by the large number of chemicals requiring assessment for potential human health and environmental impacts. Current approaches are too resource intensive in terms of time, money and animal use to evaluate all chemicals under development or already on the market. The need for timely and robust decision making demands that regulatory toxicity testing becomes more cost-effective and efficient. One way to realize this goal is by being more strategic in directing testing resources; focusing on chemicals of highest concern, limiting testing to the most probable hazards, or targeting the most vulnerable species. Hypothesis driven Integrated Approaches to Testing and Assessment (IATA) have been proposed as practical solutions to such strategic testing. In parallel, the development of the Adverse Outcome Pathway (AOP) framework, which provides information on the causal links between a molecular initiating event (MIE), intermediate key events (KEs) and an adverse outcome (AO) of regulatory concern, offers the biological context to facilitate development of IATA for regulatory decision making. This manuscript summarizes discussions at the Workshop entitled "Advancing AOPs for Integrated Toxicology and Regulatory Applications" with particular focus on the role AOPs play in informing the development of IATA for different regulatory purposes.

Insights and perspectives on emerging inputs to weight of evidence determinations for food safety: workshop proceedings

This workshop aimed to elucidate the contribution of computational and emerging in vitro methods to the weight of evidence used by risk assessors in food safety assessments. The following issues were discussed: using in silico and high-throughput screening (HTS) data to confirm the safety of approved food ingredients, applying in silico and HTS data in the process of assessing the safety of a new food ingredient, and utilizing in silico and HTS data in communicating the safety of food ingredients while enhancing the public's trust in the food supply. Perspectives on integrating computational modeling and HTS assays as well as recommendations for optimizing predictive methods for risk assessment were also provided. Given the need to act quickly or proceed cautiously as new data emerge, this workshop also focused on effectively identifying a path forward in communicating in silico and in vitro data.