Understanding mechanisms of toxicity: insights from drug discovery research

Assessment of sedative activity of fraxin: In vivo approach along with receptor binding affinity and molecular interaction with GABAergic system

Insomnia is a sleep disorder in which you have trouble falling and/or staying asleep. This research aims to evaluate the sedative effects of fraxin (FX) on sleeping mice induced by thiopental sodium (TS). In addition, a molecular docking study was conducted to investigate the molecular processes underlying these effects. The study used adult male Swiss albino mice and administered FX (10 and 20 mg/kg, i.p.) and diazepam (DZP) (2 mg/kg) either separately or in combination within the different groups to examine their modulatory effects. After a period of 30 min, the mice that had been treated were administered (TS: 20 mg/kg, i.p.) to induce sleep. The onset of sleep for the mice and the length of their sleep were manually recorded. Additionally, a computational analysis was conducted to predict the role of gamma-aminobutyric acid (GABA) receptors in the sleep process and evaluate their pharmacokinetics and toxicity. The outcomes indicated that FX extended the length of sleep and reduced the time it took to fall asleep. When the combined treatment of FX and DZP showed synergistic sedative action. Also, FX had a binding affinity of -7.2 kcal/mol, while DZP showed -8.4 kcal/mol. The pharmacokinetic investigation of FX demonstrated favorable drug-likeness and strong pharmacokinetic characteristics. Ultimately, FX demonstrated a strong sedative impact in the mouse model, likely via interacting with the GABAA receptor pathways.

A mechanistic insight into the anticancer potentials of resveratrol: Current perspectives

Resveratrol is a widely recognized polyphenolic phytochemical found in various plants and their fruits, such as peanuts, grapes, and berry fruits. It is renowned for its several health advantages. The phytochemical is well known for its anticancer properties, and a substantial amount of clinical evidence has also established its promise as a chemotherapeutic agent. This study focuses on assessing the anticancer properties of resveratrol and gaining insight into the underlying molecular mechanisms. It also evaluates the biopharmaceutical, toxicological characteristics, and clinical utilization of resveratrol to determine its suitability for further development as a reliable anticancer agent. Therefore, the information about preclinical and clinical studies was collected from different electronic databases up-to-date (2018-2023). Findings from this study revealed that resveratrol has potent therapeutic benefits against various cancers involving different molecular mechanisms, such as induction of oxidative stress, cytotoxicity, inhibition of cell migration and invasion, autophagy, arresting of the S phase of the cell cycle, apoptotic, anti-angiogenic, and antiproliferative effects by regulating different molecular pathways including PI3K/AKT, p38/MAPK/ERK, NGFR-AMPK-mTOR, and so on. However, the compound has poor oral bioavailability due to reduced absorption; this limitation is overcome by applying nanotechnology (nanoformulation of resveratrol). Clinical application also showed therapeutic benefits in several types of cancer with no serious adverse effects. We suggest additional extensive studies to further check the efficacy, safety, and long-term hazards. This could involve a larger number of clinical samples to establish the compound as a reliable drug in the treatment of cancer.

In vitro and in vivo acute toxicity of an artificial butter flavoring

Flavorings used in cookies, electronic cigarettes, popcorn, and breads contain approximately 30 chemical compounds, which makes it difficult to determine and correlate signs and symptoms of acute, subacute or chronic toxicity. The aim of this study was to characterize a butter flavoring chemically and subsequently examine the in vitro and in vivo toxicological profile using cellular techniques, invertebrates, and lab mammals. For the first time, the ethyl butanoate was found as the main compound of a butter flavoring (97.75%) and 24 h-toxicity assay employing Artemia salina larvae revealed a linear effect and LC₅₀ value of 14.7 (13.7-15.7) mg/ml (R² = 0.9448). Previous reports about higher oral doses of ethyl butanoate were not found. Observational screening with doses between 150-1000 mg/kg by gavage displayed increased amount of defecation, palpebral ptosis, and grip strength reduction, predominantly at higher doses. The flavoring also produced clinical signs of toxicity and diazepam-like behavioral changes in mice, including loss of motor coordination, muscle relaxation, increase of locomotor activity and intestinal motility, and induction of diarrhea, with deaths occurring after 48 h exposure. This substance fits into category 3 of the Globally Harmonized System. Data demonstrated that butter flavoring altered the emotional state in Swiss mice and disrupted intestinal motility, which may be a result of neurochemical changes or direct lesions in the central/peripheral nervous systems.

Non-clinical toxicity of (+)-limonene epoxide and its physio-pharmacological properties on neurological disorders

The compound (+)-limonene epoxide has antioxidant, anxiolytic, and antihelminthic properties. However, investigations to determine its long-term exposure were not performed. We investigated the systemic toxicological profile after chronic exposure as well as the antidepressant and antiepileptic potentialities of (+)-limonene epoxide on mice. Initially, we evaluated acute toxicity on Artemia salina nauplii and cytotoxicity on mice erythrocytes and peripheral blood mononuclear cells (PBMC). Aftterwards, mice were chronically treated for 120 days by gavage with (+)-limonene epoxide (25, 50, and 75 mg/kg/day) and this exposure was assessed by pathophysiological measurements. For antidepressant and anticonvulsivant analysis, we performed the forced swimming and tail suspension protocols and pentylenetetrazol- and picrotoxin-induced seizures, respectively. (+)-Limonene epoxide showed a LC50 value of 318.7 μg/mL on A. salina shrimps, caused lysis of red blood cells at higher concentrations only but did not show cytotoxicity on PMBC, which suggests pharmacological safety if plasma concentrations do not exceed 100 μg/mL. Macroscopic, hematological, clinical chemistry, and nutritional changes were not detected, though focal areas of hepatic necrosis, inflammatory infiltrate, and karyolysis have been detected at 75 mg/kg/day. The compound inhibited the developing of pentylenetetrazol- and picrotoxin-induced seizures, decreased deaths, and reduced immobility times, mainly at 75 mg/kg. So, it reversed reserpine effects, suggesting antidepressant effects should be linked to serotonergic and/or adrenergic transmission. It is feasible that (+)-limonene epoxide plays a benzodiazepine-like anticonvulsive action and may be also recommended as an antidote for poisonings caused by central depressants.

Predictive Models for Human Organ Toxicity Based on In Vitro Bioactivity Data and Chemical Structure

Traditional toxicity testing reliant on animal models is costly and low throughput, posing a significant challenge with the increasing numbers of chemicals that humans are exposed to in the environment. The purpose of this investigation was to build optimal prediction models for various human in vivo/organ-level toxicity end points (extracted from ChemIDPlus) using chemical structure and Tox21 in vitro quantitative high-throughput screening (qHTS) bioactivity assay data. Several supervised machine learning algorithms were applied to model 14 human toxicity end points pertaining to vascular, kidney, ureter and bladder, and liver organ systems. Three metrics were used to evaluate model performance: area under the receiver operating characteristic curve (AUC-ROC), balanced accuracy (BA), and Matthews correlation coefficient (MCC). The top four models, with AUC-ROC values >0.8, were derived for endocrine (0.90 ± 0.00), musculoskeletal (0.88 ± 0.02), peripheral nerve and sensation (0.85 ± 0.01), and brain and coverings (0.83 ± 0.02) toxicities, whereas the best model AUC-ROC values were >0.7 for the remaining 10 toxicities. Model performance was found to be dependent on the specific data set, model type, and feature selection method used. In addition, chemical structure and assay data showed different levels of contribution to the prediction of different toxicity end points. Although in vitro assay data, when combined with chemical structure, slightly improved the predictive accuracy for most end points (11 out of 14), a noteworthy finding was the near equal success of the structure-only models, which do not require Tox21 qHTS screening data, and the relatively poor performance of assay-only models. Thus, the top-performing structure-only models from this study could be applied for hazard screening of large sets of chemicals for potential human toxicity, whereas the largest assay contributions to models (i.e., cellular targets) could be used, along with the top-contributing structural features, to provide insight into toxicity mechanisms.

New application of the commercial sweetener rebaudioside a as a hepatoprotective candidate: Induction of the Nrf2 signaling pathway

A large population of drug candidates have failed "from bench to bed" due to unwanted toxicities. We intend to develop an alternative approach for drug discovery, that is, to seek candidates from "safe" compounds. Rebaudioside A (Reb-A) is an approved commercial sweetener from Stevia rebaudiana Bertoni. We found that Reb-A protects against carbon tetrachloride (CCl₄)-induced oxidative injury in human liver hepatocellular carcinoma (HepG2) cells. Reb-A showed antioxidant activity on reducing cellular reactive oxygen species and malondialdehyde levels while increasing glutathione levels and superoxide dismutase and catalase activities. Reb-A treatment induced nuclear factor erythroid-derived 2-like 2 (Nrf2) activation and antioxidant response element activity, as well as the expression of heme oxygenase-1 (HO-1) and NAD(P)H quinone oxidoreductase 1 (NQO1). Further mechanistic studies indicated that c-Jun N-terminal kinase (JNK), extracellular signal-regulated protein kinase (ERK), mitogen-active protein kinase (MAPK) and protein kinase C epsilon (PKCε) signaling was upregulated. Thus, the present in vitro study conclusively demonstrated that Reb-A is an activator of Nrf2 and is a potential candidate hepatoprotective agent. More importantly, the present study illustrated that seeking drug candidates from "safe" compounds is a promising strategy.

Edge effect detection for real-time cellular analyzer using statistical analysis

The Smirnov test is used to detect the edge effect, which can help technicians rapidly screen valid time-dependent cellular response curves (TCRCs) in the real time cellular analyzers (RTCA).

In vitro testing of basal cytotoxicity: Establishment of an adverse outcome pathway from chemical insult to cell death

In this paper, an in vitro basal cytotoxicity testing strategy is described for new chemical entities that lack any pre-existing information on potential toxicity. Special attention is paid to the selection of the cellular system, cytotoxicity assay and exposure conditions. This approach is based on a newly proposed generic adverse outcome pathway from chemical insult to cell death that consists of 3 steps, including initial cell injury, mitochondrial dysfunction and cell demise. The suggested strategy to consider in vitro basal cytotoxicity as a first step in evaluating the toxicity of new chemical entities can be placed in a tiered strategy that could be continued by evaluating more specific types of toxicity.

Cytotoxicity and biocompatibility of Zirconia (Y-TZP) posts with various dental cements

Objectives

Endodontically treated teeth with insufficient tooth structure are often restored with esthetic restorations. This study evaluated the cytotoxicity and biological effects of yttria partially stabilized zirconia (Y-TZP) blocks in combination with several dental cements.

Materials and Methods

Pairs of zirconia cylinders with medium alone or cemented with three types of dental cement including RelyX U200 (3M ESPE), FujiCEM 2 (GC), and Panavia F 2.0 (Kuraray) were incubated in medium for 14 days. The cytotoxicity of each supernatant was determined using 3-(4,5-dimethylthiazole-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assays on L929 fibroblasts and MC3T3-E1 osteoblasts. The levels of interleukin-6 (IL-6) mRNA were evaluated by reverse transcription polymerase chain reaction (RT-PCR), and IL-6 protein was evaluated by enzyme-linked immunosorbent assays (ELISA). The data were analyzed using one-way ANOVA and Tukey post-hoc tests. A p < 0.05 was considered statistically significant.

Results

The MTT assays showed that MC3T3-E1 osteoblasts were more susceptible to dental cements than L929 fibroblasts. The resin based dental cements increased IL-6 expression in L929 cells, but reduced IL-6 expression in MC3T3-E1 cells.

Conclusions

Zirconia alone or blocks cemented with dental cement showed acceptable biocompatibilities. The results showed resin-modified glass-ionomer based cement less produced inflammatory cytokines than other self-adhesive resin-based cements. Furthermore, osteoblasts were more susceptible than fibroblasts to the biological effects of dental cement.

Improving the prediction of organism-level toxicity through integration of chemical, protein target and cytotoxicity qHTS data

Prediction of compound toxicity is essential because covering the vast chemical space requiring safety assessment using traditional experimentally-based, resource-intensive techniques is impossible. However, such prediction is nontrivial due to the complex causal relationship between compound structure and in vivo harm. Protein target annotations and in vitro experimental outcomes encode relevant bioactivity information complementary to chemicals' structures. This work tests the hypothesis that utilizing three complementary types of data will afford predictive models that outperform traditional models built using fewer data types. A tripartite, heterogeneous descriptor set for 367 compounds was comprised of (a) chemical descriptors, (b) protein target descriptors generated using an algorithm trained on 190 000 ligand-protein interactions from ChEMBL, and (c) descriptors derived from in vitro cell cytotoxicity dose-response data from a panel of human cell lines. 100 random forests classification models for predicting rat LD50 were built using every combination of descriptors. Successive integration of data types improved predictive performance; models built using the full dataset had an average external correct classification rate of 0.82, compared to 0.73-0.80 for models built using two data types and 0.67-0.78 for models built using one. Pairwise comparisons of models trained on the same data showed that including a third data domain on top of chemistry improved average correct classification rate by 1.4-2.4 points, with p-values <0.01. Additionally, the approach enhanced the models' applicability domains and proved useful for generating novel mechanism hypotheses. The use of tripartite heterogeneous bioactivity datasets is a useful technique for improving toxicity prediction. Both protein target descriptors - which have the practical value of being derived in silico - and cytotoxicity descriptors derived from experiment are suitable contributors to such datasets.

The use of high-throughput screening in identifying chemotherapeutic agents for gastric cancer

Gastric cancer claims many lives around the world, particularly in Asia. Although diagnosis and treatment has improved, long-term survival of patients is still poor and there is an urgent need to develop more effective treatments for this disease. This review outlines some of the more innovative high-throughput screening-based approaches and strategies that may be used to identify compounds that have new or novel mechanisms of action and could be developed further as possible gastric cancer treatments in the future.

In silico assessment of adverse drug reactions and associated mechanisms

During recent years, various in silico approaches have been developed to estimate chemical and biological drug features, for example chemical fragments, protein targets, pathways, among others, that correlate with adverse drug reactions (ADRs) and explain the associated mechanisms. These features have also been used for the creation of predictive models that enable estimation of ADRs during the early stages of drug development. In this review, we discuss various in silico approaches to predict these features for a certain drug, estimate correlations with ADRs, establish causal relationships between selected features and ADR mechanisms and create corresponding predictive models.

Screening Chemicals for Estrogen Receptor Bioactivity Using a Computational Model

The U.S. Environmental Protection Agency (EPA) is considering high-throughput and computational methods to evaluate the endocrine bioactivity of environmental chemicals. Here we describe a multistep, performance-based validation of new methods and demonstrate that these new tools are sufficiently robust to be used in the Endocrine Disruptor Screening Program (EDSP). Results from 18 estrogen receptor (ER) ToxCast high-throughput screening assays were integrated into a computational model that can discriminate bioactivity from assay-specific interference and cytotoxicity. Model scores range from 0 (no activity) to 1 (bioactivity of 17β-estradiol). ToxCast ER model performance was evaluated for reference chemicals, as well as results of EDSP Tier 1 screening assays in current practice. The ToxCast ER model accuracy was 86% to 93% when compared to reference chemicals and predicted results of EDSP Tier 1 guideline and other uterotrophic studies with 84% to 100% accuracy. The performance of high-throughput assays and ToxCast ER model predictions demonstrates that these methods correctly identify active and inactive reference chemicals, provide a measure of relative ER bioactivity, and rapidly identify chemicals with potential endocrine bioactivities for additional screening and testing. EPA is accepting ToxCast ER model data for 1812 chemicals as alternatives for EDSP Tier 1 ER binding, ER transactivation, and uterotrophic assays.

Novel Uses of In Vitro Data to Develop Quantitative Biological Activity Relationship Models for in Vivo Carcinogenicity Prediction

The availability of large in vitro datasets enables better insight into the mode of action of chemicals and better identification of potential mechanism(s) of toxicity. Several studies have shown that not all in vitro assays can contribute as equal predictors of in vivo carcinogenicity for development of hybrid Quantitative Structure Activity Relationship (QSAR) models. We propose two novel approaches for the use of mechanistically relevant in vitro assay data in the identification of relevant biological descriptors and development of Quantitative Biological Activity Relationship (QBAR) models for carcinogenicity prediction. We demonstrate that in vitro assay data can be used to develop QBAR models for in vivo carcinogenicity prediction via two case studies corroborated with firm scientific rationale. The case studies demonstrate the similarities between QBAR and QSAR modeling in: (i) the selection of relevant descriptors to be used in the machine learning algorithm, and (ii) the development of a computational model that maps chemical or biological descriptors to a toxic endpoint. The results of both the case studies show: (i) improved accuracy and sensitivity which is especially desirable under regulatory requirements, and (ii) overall adherence with the OECD/REACH guidelines. Such mechanism based models can be used along with QSAR models for prediction of mechanistically complex toxic endpoints.

Towards a strategic approaches in alternative tests for pesticide safety

Pesticides have provided significant benefits including plant disease control and increased crop yields since people developed and utilized them. However, pesticide use is associated with many adverse effects, which necessitate precise toxicological tests and risk assessment. Most of these methods are based on animal studies, but considerations of animal welfare and ethics require the development of alternative methods for the evaluation of pesticide toxicity. Although the usage of laboratory animals is inevitable in scientific evaluation and alternative approaches have limitations in the whole coverage, continuous effort is necessary to minimize animal use and to develop reliable alternative tests for pesticide evaluation. This review discusses alternative approaches for pesticide toxicity tests and hazard evaluation that have been used in peer-reviewed reports and could be applied in future studies based on the critical animal research principles of reduction, replacement, and refinement.

Phenotypic screening of the ToxCast chemical library to classify toxic and therapeutic mechanisms

Addressing the safety aspects of drugs and environmental chemicals has historically been undertaken through animal testing. However, the quantity of chemicals in need of assessment and the challenges of species extrapolation require the development of alternative approaches. Our approach, the US Environmental Protection Agency's ToxCast program, utilizes a large suite of in vitro and model organism assays to interrogate important chemical libraries and computationally analyze bioactivity profiles. Here we evaluated one component of the ToxCast program, the use of primary human cell systems, by screening for chemicals that disrupt physiologically important pathways. Chemical-response signatures for 87 endpoints covering molecular functions relevant to toxic and therapeutic pathways were generated in eight cell systems for 641 environmental chemicals and 135 reference pharmaceuticals and failed drugs. Computational clustering of the profiling data provided insights into the polypharmacology and potential off-target effects for many chemicals that have limited or no toxicity information. The endpoints measured can be closely linked to in vivo outcomes, such as the upregulation of tissue factor in endothelial cell systems by compounds linked to the risk of thrombosis in vivo. Our results demonstrate that assaying complex biological pathways in primary human cells can identify potential chemical targets, toxicological liabilities and mechanisms useful for elucidating adverse outcome pathways.

Real-time bioluminescent tracking of cellular population dynamics

Cellular population dynamics are routinely monitored across many diverse fields for a variety of purposes. In general, these dynamics are assayed either through the direct counting of cellular aliquots followed by extrapolation to the total population size, or through the monitoring of signal intensity from any number of externally stimulated reporter proteins. While both viable methods, here we describe a novel technique that allows for the automated, non-destructive tracking of cellular population dynamics in real-time. This method, which relies on the detection of a continuous bioluminescent signal produced through expression of the bacterial luciferase gene cassette, provides a low cost, low time-intensive means for generating additional data compared to alternative methods.

Drug safety testing paradigm, current progress and future challenges: an overview

Early assessment of the toxicity potential of new molecules in pharmaceutical industry is a multi-dimensional task involving predictive systems and screening approaches to aid in the optimization of lead compounds prior to their entry into development phase. Due to the high attrition rate in the pharma industry in last few years, it has become imperative for the nonclinical toxicologist to focus on novel approaches which could be helpful for early screening of drug candidates. The need is that the toxicologists should change their classical approach to a more investigative approach. This review discusses the developments that allow toxicologists to anticipate safety problems and plan ways to address them earlier than ever before. This includes progress in the field of in vitro models, surrogate models, molecular toxicology, 'omics' technologies, translational safety biomarkers, stem-cell based assays and preclinical imaging. The traditional boundaries between teams focusing on efficacy/ safety and preclinical/ clinical aspects in the pharma industry are disappearing, and translational research-centric organizations with a focused vision of bringing drugs forward safely and rapidly are emerging. Today's toxicologist should collaborate with medicinal chemists, pharmacologists, and clinicians and these value-adding contributions will change traditional toxicologists from side-effect identifiers to drug development enablers.

Establishing a high-throughput and automated cancer cell proliferation panel for oncology lead optimization

Tumor cell proliferation assays are widely used for oncology drug discovery, including target validation, lead compound identification, and optimization, as well as determination of compound off-target activities. Taking advantage of robotic systems to maintain cell culture and perform cell proliferation assays would greatly increase productivity and efficiency. Here we describe the establishment of automated systems for high-throughput cell proliferation assays in a panel of 13 human tumor cell lines. These cell lines were selected from various types of human tumors containing a broad range of well-characterized mutations in multiple cellular signaling pathways. Standard procedures for cell culture and assay performance were developed and optimized in each cell line. Moreover, in-house developed software (i.e., Toolset, Curvemaster, and Biobars) was applied to analyze the data and generate data reports. Using tool compounds, we have shown that results obtained through this panel exhibit high reproducibility over a long period. Furthermore, we have demonstrated that this panel can be used to identify sensitive and insensitive cell lines for specific cancer targets, to drive cellular structure-activity relationships, and to profile compound off-target activities. All those efforts are important for cancer drug discovery lead optimization.

Mechanism-based testing strategy using in vitro approaches for identification of thyroid hormone disrupting chemicals

The thyroid hormone (TH) system is involved in several important physiological processes, including regulation of energy metabolism, growth and differentiation, development and maintenance of brain function, thermo-regulation, osmo-regulation, and axis of regulation of other endocrine systems, sexual behaviour and fertility and cardiovascular function. Therefore, concern about TH disruption (THD) has resulted in strategies being developed to identify THD chemicals (THDCs). Information on potential of chemicals causing THD is typically derived from animal studies. For the majority of chemicals, however, this information is either limited or unavailable. It is also unlikely that animal experiments will be performed for all THD relevant chemicals in the near future for ethical, financial and practical reasons. In addition, typical animal experiments often do not provide information on the mechanism of action of THDC, making it harder to extrapolate results across species. Relevant effects may not be identified in animal studies when the effects are delayed, life stage specific, not assessed by the experimental paradigm (e.g., behaviour) or only occur when an organism has to adapt to environmental factors by modulating TH levels. Therefore, in vitro and in silico alternatives to identify THDC and quantify their potency are needed. THDC have many potential mechanisms of action, including altered hormone production, transport, metabolism, receptor activation and disruption of several feed-back mechanisms. In vitro assays are available for many of these endpoints, and the application of modern '-omics' technologies, applicable for in vivo studies can help to reveal relevant and possibly new endpoints for inclusion in a targeted THDC in vitro test battery. Within the framework of the ASAT initiative (Assuring Safety without Animal Testing), an international group consisting of experts in the areas of thyroid endocrinology, toxicology of endocrine disruption, neurotoxicology, high-throughput screening, computational biology, and regulatory affairs has reviewed the state of science for (1) known mechanisms for THD plus examples of THDC; (2) in vitro THD tests currently available or under development related to these mechanisms; and (3) in silico methods for estimating the blood levels of THDC. Based on this scientific review, the panel has recommended a battery of test methods to be able to classify chemicals as of less or high concern for further hazard and risk assessment for THD. In addition, research gaps and needs are identified to be able to optimize and validate the targeted THD in vitro test battery for a mechanism-based strategy for a decision to opt out or to proceed with further testing for THD.

A label-free, impedance-based real time assay to identify drug-induced toxicities and differentiate cytostatic from cytotoxic effects

Cell-based assays are key tools in drug safety assessment. However, they usually provide only limited information about time-kinetics of a toxic effect and implementing multiple measurements is often complex. To overcome these issues we established an impedance-based approach which is able to differentiate cytostatic from cytotoxic drugs by recording time-kinetics of compound-effects on cells. NIH 3T3 fibroblasts were seeded on xCELLigence® E-plates and impedance was continuously measured over 5 days. The obtained results reflected cytotoxicity and cell proliferation, as confirmed by neutral red uptake in vitro. Based on known toxicants, we established an algorithm able to discriminate cytostatic, cytotoxic and non-toxic compounds based on the shape of the impedance curves. Analyzing impedance curve patterns of additional 37 compounds allowed the identification and differentiation of these distinct effects as results correlated well with previous in vivo findings. We show that impedance-based real-time cell analysis is a convenient tool to characterize and discriminate effects of compounds on cells in a time-dependent and label-free manner. The presented impedance assay could be used to further characterize toxicities observed in vivo or in vitro. Due to the ease of performance it may also be a suitable screening tool.

Organotypic liver culture models: meeting current challenges in toxicity testing

Prediction of chemical-induced hepatotoxicity in humans from in vitro data continues to be a significant challenge for the pharmaceutical and chemical industries. Generally, conventional in vitro hepatic model systems (i.e. 2-D static monocultures of primary or immortalized hepatocytes) are limited by their inability to maintain histotypic and phenotypic characteristics over time in culture, including stable expression of clearance and bioactivation pathways, as well as complex adaptive responses to chemical exposure. These systems are less than ideal for longer-term toxicity evaluations and elucidation of key cellular and molecular events involved in primary and secondary adaptation to chemical exposure, or for identification of important mediators of inflammation, proliferation and apoptosis. Progress in implementing a more effective strategy for in vitro-in vivo extrapolation and human risk assessment depends on significant advances in tissue culture technology and increasing their level of biological complexity. This article describes the current and ongoing need for more relevant, organotypic in vitro surrogate systems of human liver and recent efforts to recreate the multicellular architecture and hemodynamic properties of the liver using novel culture platforms. As these systems become more widely used for chemical and drug toxicity testing, there will be a corresponding need to establish standardized testing conditions, endpoint analyses and acceptance criteria. In the future, a balanced approach between sample throughput and biological relevance should provide better in vitro tools that are complementary with animal testing and assist in conducting more predictive human risk assessment.

Update on EPA's ToxCast program: providing high throughput decision support tools for chemical risk management

The field of toxicology is on the cusp of a major transformation in how the safety and hazard of chemicals are evaluated for potential effects on human health and the environment. Brought on by the recognition of the limitations of the current paradigm in terms of cost, time, and throughput, combined with the ever increasing power of modern biological tools to probe mechanisms of chemical-biological interactions at finer and finer resolutions, 21st century toxicology is rapidly taking shape. A key element of the new approach is a focus on the molecular and cellular pathways that are the targets of chemical interactions. By understanding toxicity in this manner, we begin to learn how chemicals cause toxicity, as opposed to merely what diseases or health effects they might cause. This deeper understanding leads to increasing confidence in identifying which populations might be at risk, significant susceptibility factors, and key influences on the shape of the dose-response curve. The U. S. Environmental Protection Agency (EPA) initiated the ToxCast, or "toxicity forecaster", program 5 years ago to gain understanding of the strengths and limitations of the new approach by starting to test relatively large numbers (hundreds) of chemicals against an equally large number of biological assays. Using computational approaches, the EPA is building decision support tools based on ToxCast in vitro screening results to help prioritize chemicals for further investigation, as well as developing predictive models for a number of health outcomes. This perspective provides a summary of the initial, proof of concept, Phase I of ToxCast that has laid the groundwork for the next phases and future directions of the program.

Survey of public domain software for docking simulations and virtual screening

Progress in functional genomics and structural studies on biological macromolecules are generating a growing number of potential targets for therapeutics, adding to the importance of computational approaches for small molecule docking and virtual screening of candidate compounds. In this review, recent improvements in several public domain packages that are widely used in the context of drug development, including DOCK, AutoDock, AutoDock Vina and Screening for Ligands by Induced-fit Docking Efficiently (SLIDE) are surveyed. The authors also survey methods for the analysis and visualisation of docking simulations, as an important step in the overall assessment of the results. In order to illustrate the performance and limitations of current docking programs, the authors used the National Center for Toxicological Research (NCTR) oestrogen receptor benchmark set of 232 oestrogenic compounds with experimentally measured strength of binding to oestrogen receptor alpha. The methods tested here yielded a correlation coefficient of up to 0.6 between the predicted and observed binding affinities for active compounds in this benchmark.

Molecular dynamics

Molecular dynamics (MD) simulation holds the promise of revealing the mechanisms of biological processes in their ultimate detail. It is carried out by computing the interaction forces acting on each atom and then propagating the velocities and positions of the atoms by numerical integration of Newton's equations of motion. In this review, we present an overview of how the MD simulation can be conducted to address computational toxicity problems. The study cases will cover a standard MD simulation performed to investigate the overall flexibility of a cytochrome P450 (CYP) enzyme and a set of more advanced MD simulations to examine the barrier to ion conduction in a human α7 nicotinic acetylcholine receptor (nAChR).

Adaptation of high-throughput screening in drug discovery-toxicological screening tests

High-throughput screening (HTS) is one of the newest techniques used in drug design and may be applied in biological and chemical sciences. This method, due to utilization of robots, detectors and software that regulate the whole process, enables a series of analyses of chemical compounds to be conducted in a short time and the affinity of biological structures which is often related to toxicity to be defined. Since 2008 we have implemented the automation of this technique and as a consequence, the possibility to examine 100,000 compounds per day. The HTS method is more frequently utilized in conjunction with analytical techniques such as NMR or coupled methods e.g., LC-MS/MS. Series of studies enable the establishment of the rate of affinity for targets or the level of toxicity. Moreover, researches are conducted concerning conjugation of nanoparticles with drugs and the determination of the toxicity of such structures. For these purposes there are frequently used cell lines. Due to the miniaturization of all systems, it is possible to examine the compound's toxicity having only 1-3 mg of this compound. Determination of cytotoxicity in this way leads to a significant decrease in the expenditure and to a reduction in the length of the study.

In vitro safety pharmacology profiling: what else beyond hERG?

One of the main reasons for drug failures in clinical development, or postmarket launch, is lacking or compromised safety margins at therapeutic doses. Organ toxicity with poorly defined mechanisms and adverse drug reactions associated with on- and off-target effects are the major contributors to safety-related shortfalls of many clinical drug candidates. Therefore, to avoid high attrition rates in clinical trials, it is imperative to test compounds for potential adverse reactions during early drug discovery. Beyond a small number of targets associated with clinically acknowledged adverse drug reactions, there is little consensus on other targets that are important to consider at an early stage for in vitro safety pharmacology assessment. We consider here a limited number of safety-related targets, from different target families, which were selected as part of in vitro safety pharmacology profiling panels integrated in the drug-development process at Novartis. The best way to assess these targets, using a biochemical or a functional readout, is discussed. In particular, the importance of using cell-based profiling assays for the characterization of an agonist action at some GPCRs is highlighted. A careful design of in vitro safety pharmacology profiling panels allows better prediction of potential adverse effects of new chemical entities early in the drug-discovery process. This contributes to the selection of the best candidate for clinical development and, ultimately, should contribute to a decreased attrition rate.

Alternative (non-animal) methods for cosmetics testing: current status and future prospects-2010

The 7th amendment to the EU Cosmetics Directive prohibits to put animal-tested cosmetics on the market in Europe after 2013. In that context, the European Commission invited stakeholder bodies (industry, non-governmental organisations, EU Member States, and the Commission's Scientific Committee on Consumer Safety) to identify scientific experts in five toxicological areas, i.e. toxicokinetics, repeated dose toxicity, carcinogenicity, skin sensitisation, and reproductive toxicity for which the Directive foresees that the 2013 deadline could be further extended in case alternative and validated methods would not be available in time. The selected experts were asked to analyse the status and prospects of alternative methods and to provide a scientifically sound estimate of the time necessary to achieve full replacement of animal testing. In summary, the experts confirmed that it will take at least another 7-9 years for the replacement of the current in vivo animal tests used for the safety assessment of cosmetic ingredients for skin sensitisation. However, the experts were also of the opinion that alternative methods may be able to give hazard information, i.e. to differentiate between sensitisers and non-sensitisers, ahead of 2017. This would, however, not provide the complete picture of what is a safe exposure because the relative potency of a sensitiser would not be known. For toxicokinetics, the timeframe was 5-7 years to develop the models still lacking to predict lung absorption and renal/biliary excretion, and even longer to integrate the methods to fully replace the animal toxicokinetic models. For the systemic toxicological endpoints of repeated dose toxicity, carcinogenicity and reproductive toxicity, the time horizon for full replacement could not be estimated.

The use of real-time cell analyzer technology in drug discovery: defining optimal cell culture conditions and assay reproducibility with different adherent cellular models

The use of impedance-based label-free technology applied to drug discovery is nowadays receiving more and more attention. Indeed, such a simple and noninvasive assay that interferes minimally with cell morphology and function allows one to perform kinetic measurements and to obtain information on proliferation, migration, cytotoxicity, and receptor-mediated signaling. The objective of the study was to further assess the usefulness of a real-time cell analyzer (RTCA) platform based on impedance in the context of quality control and data reproducibility. The data indicate that this technology is useful to determine the best coating and cellular density conditions for different adherent cellular models including hepatocytes, cardiomyocytes, fibroblasts, and hybrid neuroblastoma/neuronal cells. Based on 31 independent experiments, the reproducibility of cell index data generated from HepG2 cells exposed to DMSO and to Triton X-100 was satisfactory, with a coefficient of variation close to 10%. Cell index data were also well reproduced when cardiomyocytes and fibroblasts were exposed to 21 compounds three times (correlation >0.91, p < 0.0001). The data also show that a cell index decrease is not always associated with cytotoxicity effects and that there are some confounding factors that can affect the analysis. Finally, another drawback is that the correlation analysis between cellular impedance measurements and classical toxicity endpoints has been performed on a limited number of compounds. Overall, despite some limitations, the RTCA technology appears to be a powerful and reliable tool in drug discovery because of the reasonable throughput, rapid and efficient performance, technical optimization, and cell quality control.

Use of in vitro HTS-derived concentration-response data as biological descriptors improves the accuracy of QSAR models of in vivo toxicity

BACKGROUND

Quantitative high-throughput screening (qHTS) assays are increasingly being used to inform chemical hazard identification. Hundreds of chemicals have been tested in dozens of cell lines across extensive concentration ranges by the National Toxicology Program in collaboration with the National Institutes of Health Chemical Genomics Center.

OBJECTIVES

Our goal was to test a hypothesis that dose-response data points of the qHTS assays can serve as biological descriptors of assayed chemicals and, when combined with conventional chemical descriptors, improve the accuracy of quantitative structure-activity relationship (QSAR) models applied to prediction of in vivo toxicity end points.

METHODS

We obtained cell viability qHTS concentration-response data for 1,408 substances assayed in 13 cell lines from PubChem; for a subset of these compounds, rodent acute toxicity half-maximal lethal dose (LD50) data were also available. We used the k nearest neighbor classification and random forest QSAR methods to model LD50 data using chemical descriptors either alone (conventional models) or combined with biological descriptors derived from the concentration-response qHTS data (hybrid models). Critical to our approach was the use of a novel noise-filtering algorithm to treat qHTS data.

RESULTS

Both the external classification accuracy and coverage (i.e., fraction of compounds in the external set that fall within the applicability domain) of the hybrid QSAR models were superior to conventional models.

CONCLUSIONS

Concentration-response qHTS data may serve as informative biological descriptors of molecules that, when combined with conventional chemical descriptors, may considerably improve the accuracy and utility of computational approaches for predicting in vivo animal toxicity end points.

Comparison of MTT assay, flow cytometry, and RT-PCR in the evaluation of cytotoxicity of five prosthodontic materials

In the present study, the cytotoxic effects of five prosthodontic materials on the L929 cell line were assessed by flow cytometry (FCM), reverse transcription PCR (RT-PCR), and MTT (3-(4,5-dimethylthiazole-2-yl)-2,5-diphenyltetrazoli-umbromide) assay. The cells were treated with eluates resin (RE), pressable ceramics (PC), Co-Cr alloy-porcelain (CC), Ni-Cr alloy-porcelain (NC), and diatomite ceramics (DC). The cytotoxicity of all the materials tested by the MTT assay was grade 1. By FCM analysis, apoptosis rates of DC and PC were low, with no significant difference from the control (p > 0.05). The rest of the groups induced much higher apoptosis rates (p < 0.05), with the highest in the RE group. The necrotic cell levels of RE was also significantly increased (p < 0.05). Bcl-2 and Bax mRNA expression were determined by RT-PCR, and the Bax/Bcl-2 ratio in the DC and PC groups were not significantly different from the control (p > 0.05), whereas CC, NC, and RE groups showed significant differences (p < 0.05). Taken together, the results suggest that FCM and RT-PCR analyses can supplement the traditional MTT assay in evaluating the cytotoxicity of prosthodontic materials for selecting highly biocompatible materials.

Computational toxicology: realizing the promise of the toxicity testing in the 21st century

BACKGROUND

The National Academies' Standing Committee on Use of Emerging Science for Environmental Health Decisions held a meeting (21-22 September 2009 in Washington, DC) titled "Computational Toxicology: From Data to Analyses to Applications." This commentary reflects on the presentations and roundtable discussions from the meeting that were designed to review the state of the art in the field and the practical applications of the new science and to provide focus to the field.

OBJECTIVES

The meeting considered two topics: the emerging data streams amenable to computational modeling and data mining, and the emerging data analysis and modeling tools.

DISCUSSION

Computational toxicology is a subdiscipline of toxicology that aims to use the mathematical, statistical, modeling, and computer science tools to better understand the mechanisms through which a given chemical induces harm and, ultimately, to be able to predict adverse effects of the toxicants on human health and/or the environment. The participants stressed the importance of computational toxicology to the future of environmental health sciences and regulatory decisions in public health; however, many challenges remain to be addressed before the findings from high-throughput screens and in silico models may be considered sufficiently robust and informative.

CONCLUSIONS

Many scientists, regulators, and the general public believe that new and better ways to assess human toxicity are now needed, and technological breakthroughs are empowering the field of toxicity assessment. Even though the application of computational toxicology to environmental health decisions requires additional efforts, the merger of the power of computers with biological information is poised to deliver new tools and knowledge.

FTIR spectral signature of the effect of cardiotonic steroids with antitumoral properties on a prostate cancer cell line

We show in the present work that the infrared (IR) spectrum of human PC-3 prostate cancer cells exposed to anticancer drugs could offer a unique opportunity to get a fingerprint of all the major biochemical components (DNA, RNA, proteins, lipids, etc.) present in the cells and to identify with high sensitivity the signature of the metabolic changes induced by anticancer drugs. We investigated here the FTIR-related signatures of the effect of 4 structurally-related cardiotonic steroids (CS), i.e. ouabain, 19-hydroxy-2″-oxovoruscharin, hellebrin and 19-hydroxy-hellebrin on PC-3 cancer cells incubated between 0 and 36 h in the absence (control) or the presence of the CS. For each molecule a single spectral signature described the largest part of the time dependent modifications with a possible very minor second component. The spectral signatures characterizing the effects of each of the four CS were unique but very similar when compared to the signature of the effect of an intercalating anticancer drug, i.e. doxorubicin, selected as a positive reference compound in our study, suggesting a fully distinct set of cellular perturbations. The current study thus illustrates that Fourier Transform Infrared (FTIR) analyses can be used to identify, among the perturbations induced on a given cancer cell line, the features common to a group of anticancer compounds as well as features specific to every single drug.

Impact of environmental chemicals on key transcription regulators and correlation to toxicity end points within EPA's ToxCast program

Exposure to environmental chemicals adds to the burden of disease in humans and wildlife to a degree that is difficult to estimate and, thus, mitigate. The ability to assess the impact of existing chemicals for which little to no toxicity data are available or to foresee such effects during early stages of chemical development and use, and before potential exposure occurs, is a pressing need. However, the capacity of the current toxicity evaluation approaches to meet this demand is limited by low throughput and high costs. In the context of EPA's ToxCast project, we have evaluated a novel cellular biosensor system (Factorial (1) ) that enables rapid, high-content assessment of a compound's impact on gene regulatory networks. The Factorial biosensors combined libraries of cis- and trans-regulated transcription factor reporter constructs with a highly homogeneous method of detection enabling simultaneous evaluation of multiplexed transcription factor activities. Here, we demonstrate the application of the technology toward determining bioactivity profiles by quantitatively evaluating the effects of 309 environmental chemicals on 25 nuclear receptors and 48 transcription factor response elements. We demonstrate coherent transcription factor activity across nuclear receptors and their response elements and that Nrf2 activity, a marker of oxidative stress, is highly correlated to the overall promiscuity of a chemical. Additionally, as part of the ToxCast program, we identify molecular targets that associate with in vivo end points and represent modes of action that can serve as potential toxicity pathway biomarkers and inputs for predictive modeling of in vivo toxicity.

Defining desirable central nervous system drug space through the alignment of molecular properties, in vitro ADME, and safety attributes

As part of our effort to increase survival of drug candidates and to move our medicinal chemistry design to higher probability space for success in the Neuroscience therapeutic area, we embarked on a detailed study of the property space for a collection of central nervous system (CNS) molecules. We carried out a thorough analysis of properties for 119 marketed CNS drugs and a set of 108 Pfizer CNS candidates. In particular, we focused on understanding the relationships between physicochemical properties, in vitro ADME (absorption, distribution, metabolism, and elimination) attributes, primary pharmacology binding efficiencies, and in vitro safety data for these two sets of compounds. This scholarship provides guidance for the design of CNS molecules in a property space with increased probability of success and may lead to the identification of druglike candidates with favorable safety profiles that can successfully test hypotheses in the clinic.

A high-throughput respirometric assay for mitochondrial biogenesis and toxicity

Mitochondria are a common target of toxicity for drugs and other chemicals and result in decreased aerobic metabolism and cell death. In contrast, mitochondrial biogenesis restores cell vitality, and there is a need for new agents to induce biogenesis. Current cell-based models of mitochondrial biogenesis or toxicity are inadequate because cultured cell lines are highly glycolytic with minimal aerobic metabolism and altered mitochondrial physiology. In addition, there are no high-throughput real-time assays that assess mitochondrial function. We adapted primary cultures of renal proximal tubular cells (RPTCs) that exhibit in vivo levels of aerobic metabolism, are not glycolytic, and retain higher levels of differentiated functions and used the Seahorse Bioscience analyzer to measure mitochondrial function in real time in multiwell plates. Using uncoupled respiration as a marker of electron transport chain (ETC) integrity, the nephrotoxicants cisplatin, HgCl(2), and gentamicin exhibited mitochondrial toxicity prior to decreases in basal respiration and cell death. Conversely, using FCCP (carbonylcyanide p-trifluoromethoxyphenylhydrazone)-uncoupled respiration as a marker of maximal ETC activity, 1-(2,5-dimethoxy-4-iodophenyl)-2-aminopropane (DOI), SRT1720, resveratrol, daidzein, and metformin produced mitochondrial biogenesis in RPTCs. The merger of the RPTC model and multiwell respirometry results in a single high-throughput assay to measure mitochondrial biogenesis and toxicity and nephrotoxic potential.

Computational toxicology as implemented by the U.S. EPA: providing high throughput decision support tools for screening and assessing chemical exposure, hazard and risk

Computational toxicology is the application of mathematical and computer models to help assess chemical hazards and risks to human health and the environment. Supported by advances in informatics, high-throughput screening (HTS) technologies, and systems biology, the U.S. Environmental Protection Agency EPA is developing robust and flexible computational tools that can be applied to the thousands of chemicals in commerce, and contaminant mixtures found in air, water, and hazardous-waste sites. The Office of Research and Development (ORD) Computational Toxicology Research Program (CTRP) is composed of three main elements. The largest component is the National Center for Computational Toxicology (NCCT), which was established in 2005 to coordinate research on chemical screening and prioritization, informatics, and systems modeling. The second element consists of related activities in the National Health and Environmental Effects Research Laboratory (NHEERL) and the National Exposure Research Laboratory (NERL). The third and final component consists of academic centers working on various aspects of computational toxicology and funded by the U.S. EPA Science to Achieve Results (STAR) program. Together these elements form the key components in the implementation of both the initial strategy, A Framework for a Computational Toxicology Research Program (U.S. EPA, 2003), and the newly released The U.S. Environmental Protection Agency's Strategic Plan for Evaluating the Toxicity of Chemicals (U.S. EPA, 2009a). Key intramural projects of the CTRP include digitizing legacy toxicity testing information toxicity reference database (ToxRefDB), predicting toxicity (ToxCast) and exposure (ExpoCast), and creating virtual liver (v-Liver) and virtual embryo (v-Embryo) systems models. U.S. EPA-funded STAR centers are also providing bioinformatics, computational toxicology data and models, and developmental toxicity data and models. The models and underlying data are being made publicly available through the Aggregated Computational Toxicology Resource (ACToR), the Distributed Structure-Searchable Toxicity (DSSTox) Database Network, and other U.S. EPA websites. While initially focused on improving the hazard identification process, the CTRP is placing increasing emphasis on using high-throughput bioactivity profiling data in systems modeling to support quantitative risk assessments, and in developing complementary higher throughput exposure models. This integrated approach will enable analysis of life-stage susceptibility, and understanding of the exposures, pathways, and key events by which chemicals exert their toxicity in developing systems (e.g., endocrine-related pathways). The CTRP will be a critical component in next-generation risk assessments utilizing quantitative high-throughput data and providing a much higher capacity for assessing chemical toxicity than is currently available.

The future of toxicity testing

In 2007, the U.S. National Research Council (NRC) released a report, "Toxicity Testing in the 21st Century: A Vision and a Strategy," that proposes a paradigm shift for toxicity testing of environmental agents. The vision is based on the notion that exposure to environmental agents leads to adverse health outcomes through the perturbation of toxicity pathways that are operative in humans. Implementation of the NRC vision will involve a fundamental change in the assessment of toxicity of environmental agents, moving away from adverse health outcomes observed in experimental animals to the identification of critical perturbations of toxicity pathways. Pathway perturbations will be identified using in vitro assays and quantified for dose response using methods in computational toxicology and other recent scientific advances in basic biology. Implementation of the NRC vision will require a major research effort, not unlike that required to successfully map the human genome, extending over 10 to 20 years, involving the broad scientific community to map important toxicity pathways operative in humans. This article provides an overview of the scientific tools and technologies that will form the core of the NRC vision for toxicity testing. Of particular importance will be the development of rapidly performed in vitro screening assays using human cells and cell lines or human tissue surrogates to efficiently identify environmental agents producing critical pathway perturbations. In addition to the overview of the NRC vision, this study documents the reaction by a number of stakeholder groups since 2007, including the scientific, risk assessment, regulatory, and animal welfare communities.

Predictive Toxicology Approaches for Small Molecule Oncology Drugs

A daunting, unmet medical need exists for effective oncology chemotherapies, with cancer deaths in 2009 to exceed 560,000 in the United States alone. Because of the rapid demise of the majority of cancer patients with metastatic disease, oncology drug development must follow a much different paradigm than therapeutic candidates for less onerous diseases. The majority of drug candidates in development today are targeted at cancer therapy. Many of these candidate chemotherapeutic agents are active against novel targets, often presenting unique toxicological profiles. Since many of these novel targets are not unique to cancer cells, therapeutic margins may not exist. Decision making, in this event, is among the most challenging that any pharmaceutical toxicologist/pathologist or regulator will face. Nonclinical development scientists must compress timelines to present therapeutic options for cancer patients who have failed conventional therapy. In support of this goal, the U. S. Food and Drug Administration has created an oncology-specific paradigm for nonclinical testing and has introduced strategies to accelerate development and approval of successful candidates. Pharmaceutical toxicology testing strategies must not only satisfy regulation as the minimal expectation, but also attempt to reduce the current high attrition rates for oncologic candidates. A successful toxicology testing strategy represents the substance of this treatise.

The methods of identification, analysis, and removal of endocrine disrupting compounds (EDCs) in water

The information regarding endocrine disrupting compounds (EDCs) was reviewed, including the definition and characteristics, the recent research trends concerning identification and analytical methods, and the applicable removal processes. EDCs include various types of natural and synthetic chemical compounds presenting the mimicking or inhibition of the reproductive action of the endocrine system in animals and humans. The ubiquitous presence with trace level concentrations and the wide diversity are the reported characteristics of EDCs. Biologically based assays seem to be a promising method for the identification of EDCs. On the other hand, mass-based analytical methods show excellent sensitivity and precision for their quantification. Several extraction techniques for the instrumental analysis have been developed since they are crucial in determining overall analytical performances. Conventional treatment techniques, including coagulation, precipitation, and activated sludge processes, may not be highly effective in removing EDCs, while the advanced treatment options, such as granular activated carbon (GAC), membrane, and advanced oxidation processes (AOPs), have shown satisfactory results. The oxidative degradation of some EDCs was associated with aromatic moieties in their structure. Further studies on EDCs need to be conducted, such as source reduction, limiting exposure to vulnerable populations, treatment or remediation of contaminated sites, and the detailed understanding of transport mechanisms in the environment.

Evaluation of high-throughput genotoxicity assays used in profiling the US EPA ToxCast chemicals

Three high-throughput screening (HTS) genotoxicity assays-GreenScreen HC GADD45a-GFP (Gentronix Ltd.), CellCiphr p53 (Cellumen Inc.) and CellSensor p53RE-bla (Invitrogen Corp.)-were used to analyze the collection of 320 predominantly pesticide active compounds being tested in Phase I of US. Environmental Protection Agency's ToxCast research project. Between 9% and 12% of compounds were positive for genotoxicity in the assays. However, results of the varied tests only partially overlapped, suggesting a strategy of combining data from a battery of assays. The HTS results were compared to mutagenicity (Ames) and animal tumorigenicity data. Overall, the HTS assays demonstrated low sensitivity for rodent tumorigens, likely due to: screening at a low concentration, coverage of selected genotoxic mechanisms, lack of metabolic activation and difficulty detecting non-genotoxic carcinogens. Conversely, HTS results demonstrated high specificity, >88%. Overall concordance of the HTS assays with tumorigenicity data was low, around 50% for all tumorigens, but increased to 74-78% (vs. 60% for Ames) for those compounds producing tumors in rodents at multiple sites and, thus, more likely genotoxic carcinogens. The aim of the present study was to evaluate the utility of HTS assays to identify potential genotoxicity hazard in the larger context of the ToxCast project, to aid prioritization of environmentally relevant chemicals for further testing and assessment of carcinogenicity risk to humans.

Cellular stress response pathway system as a sentinel ensemble in toxicological screening

High costs, long test times, and societal concerns related to animal use have required the development of in vitro assays for the rapid and cost-effective toxicological evaluation and characterization of compounds in both the pharmaceutical and environmental arenas. Although the pharmaceutical industry has developed very effective, high-throughput in vitro assays for determining the therapeutic potential of compounds, the application of this approach to toxicological screening has been limited. A primary reason for this is that while drug candidate screens are directed to a specific target/mechanism, xenobiotics can cause toxicity through any of a myriad of undefined interactions with cellular components and processes. Given that it is not practical to design assays that can interrogate each potential toxicological target, an integrative approach is required if there is to be a rapid and low-cost toxicological evaluation of chemicals. Cellular stress response pathways offer a viable solution to the creation of a set of integrative assays as there is a limited and hence manageable set (a small ensemble of 10 or less) of major cellular stress response pathways through which cells mount a homoeostatic response to toxicants and which also participate in cell fate/death decisions. Further, over the past decades, these pathways have been well characterized at a molecular level thereby enabling the development of high-throughput cell-based assays using the components of the pathways. Utilization of the set of cellular stress response pathway-based assays as indicators of toxic interactions of chemicals with basic cellular machinery will potentially permit the clustering of chemicals based on biological response profiles of common mode of action (MOA) and also the inference of the specific MOA of a toxicant. This article reviews the biochemical characteristics of the stress response pathways, their common architecture that enables rapid activation during stress, their participation in cell fate decisions, the essential nature of these pathways to the organism, and the biochemical basis of their cross-talk that permits an assay ensemble screening approach. Subsequent sections describe how the stress pathway ensemble assay approach could be applied to screening potentially toxic compounds and discuss how this approach may be used to derive toxicant MOA from the biological activity profiles that the ensemble strategy provides. The article concludes with a review of the application of the stress assay concept to noninvasive in vivo assessments of chemical toxicants.