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Overall, the results of the 7 participating laboratories are quite similar. After exposing Calu-3 alone and Calu-3 co-cultures with macrophages, no effects of lipopolysaccharide (LPS), quartz (DQ12) or titanium dioxide (TiO2) NM-105 particles on the cell viability and barrier integrity were detected. LPS exposure induced moderate cytokine release in the Calu-3 monoculture, albeit not statistically significant in most labs. In the co-culture models, most laboratories showed that LPS can significantly induce cytokine release (IL-6, IL-8 and TNF-α). The exposure to quartz and TiO2 particles did not induce a statistically significant increase in cytokine release in both cell models probably due to our relatively low deposited doses, which were inspired by in vivo dose levels. The intra- and inter-laboratory comparison study indicated acceptable interlaboratory variation for cell viability/toxicity (WST-1, LDH) and transepithelial electrical resistance, and relatively high inter-laboratory variation for cytokine production.

Cell-based metabolomics provides multiparametric physiologically relevant readouts that can be highly advantageous for improved, biologically based decision making in early stages of compound development. Here, we present the development of a 96-well plate LC-MS/MS-based targeted metabolomics screening platform for the classification of liver toxicity modes of action (MoAs) in HepG2 cells. Different parameters of the workflow (cell seeding density, passage number, cytotoxicity testing, sample preparation, metabolite extraction, analytical method, and data processing) were optimized and standardized to increase the efficiency of the testing platform. The applicability of the system was tested with seven substances known to be representative of three different liver toxicity MoAs (peroxisome proliferation, liver enzyme induction, and liver enzyme inhibition). Five concentrations per substance, aimed at covering the complete dose-response curve, were analyzed and 221 uniquely identified metabolites were measured, annotated, and allocated in 12 different metabolite classes such as amino acids, carbohydrates, energy metabolism, nucleobases, vitamins and cofactors, and diverse lipid classes. Multivariate and univariate analyses showed a dose response of the metabolic effects, a clear differentiation between liver toxicity MoAs and resulted in the identification of metabolite patterns specific for each MoA. Key metabolites indicative of both general and mechanistic specific hepatotoxicity were identified. The method presented here offers a multiparametric, mechanistic-based, and cost-effective hepatotoxicity screening that provides MoA classification and sheds light into the pathways involved in the toxicological mechanism. This assay can be implemented as a reliable compound screening platform for improved safety assessment in early compound development pipelines. Graphical abstract

Analog zum Periodensystem, das Elemente nach ihrer Ähnlichkeit der Strukturen und chemischen Eigenschaften gruppiert, kann die Gefahr chemischer Stoffe in Gruppen mit ähnlichen Strukturen und ähnlichen toxikologischen Eigenschaften bewertet werden. Im Folgenden werden Fallbeispiele zu Gruppierungsstrategien vorgestellt, welche die Bewertungen von Gefahr, Exposition und Risiko für die menschliche Gesundheit unterstützen. Sowohl unter EU‐REACh als auch im US‐TSCA New Chemicals Programm ist in der Regel die strukturelle Ähnlichkeit die Grundlage für eine Gruppierungt. Allerdings ist dieses Kriterium nicht immer angemessen und ausreichend. Auf der Grundlage der gewonnenen Erkenntnisse leiten wir zehn Grundsätze für die Gruppierung ab, darunter: die transparente Darstellung des Zwecks der Gruppierung, die Definition der Kriterien für eine Gruppierung und die Grenzen der Gruppen, eine dieEinbeziehung oder der Ausschluss eines Stoffs in oder aus einer Gruppe aufgrund toxikologischer Eigenschaften und eine Begründung der Zuordnung durch robuste Daten aus angemessenen Methoden. Diese Grundsätze gelten sowohl für eine erste Gruppierung zur Priorisierung weiterer Maßnahmen als auch für die endgültige Gruppierung zur Gewinnung von Daten für die Risikobewertung. Beides kann ein effektives Risikomanagement forcieren.

The establishment of reliable and robust in vitro models for hazard assessment, moving away from animal testing, requires evaluation of model transferability and reproducibility. Lung models that can be exposed via the air, by means of an air-liquid interface are promising in vitro models for evaluating the safety of nanomaterials (NMs) after inhalation exposure. We performed an inter-laboratory comparison study to evaluate the transferability and reproducibility of a lung model consisting of the human bronchial cell line Calu-3 as monoculture and, to increase the relevance of the model, also as co-culture with macrophages (derived from the THP-1 monocyte cell line or from human blood monocytes). Exposure employed the VITROCELL® Cloud12 system at physiologically relevant doses. Overall, the results of the seven participating laboratories are quite similar. No effects of lipopolysaccharide (LPS), quartz (DQ12) or titanium dioxide (TiO2) NM-105 exposure on cell viability and barrier integrity were seen in the monoculture and co-culture models. Most laboratories showed that LPS induced cytokine release in the co-culture models, but not the monoculture model. Exposure to DQ12 or TiO2 did not increase cytokine release, probably due to too low deposited doses. Interlaboratory variability indicated acceptable variation for cell viability measurements and relatively high variation for cytokine measurements. Based on the transferability and reproducibility of the model and its air exposure we are confident that, based on detailed SOPs, performing a new round of interlaboratory comparison, and increasing the deposited doses of NMs, these models may be taken further towards a possible OECD guideline.

Nominal concentrations (

In analogy to the periodic system that groups elements by their similarity in structure and chemical properties, the hazard of chemicals can be assessed in groups of similar structures and similar toxicological properties. Here we review case studies of grouping strategies that supported the assessment of hazard, exposure, and risk to human health. By the EU-REACh and the US-TSCA New Chemicals Program, structural similarity is commonly used as the basis for grouping, but that criterion is not always adequate and sufficient. Based on the lessons learned, we derive ten principles for grouping, including: transparency of the purpose, criteria and boundaries of the group; adequacy of methods used to justify the group; inclusion or exclusion of substances in the group by toxicological properties. These principles apply to initial grouping to prioritize further actions as well as to definitive grouping to generate data for risk assessment. Both can expedite effective risk management.

The oral uptake of nanoparticles is an important route of human exposure and requires solid models for hazard assessment. While the systemic availability is generally low, ingestion may not only affect gastrointestinal tissues but also intestinal microbes. The gut microbiota contributes essentially to human health, whereas gut microbial dysbiosis is known to promote several intestinal and extra-intestinal diseases. Gut microbiota-derived metabolites, which are found in the blood stream, serve as key molecular mediators of host metabolism and immunity.Gut microbiota and the plasma metabolome were analyzed in male Wistar rats receiving either SiOThe combined profiling of intestinal microbiome and plasma metabolome may serve as an early and sensitive indicator of gut microbiome changes induced by orally administered nanoparticles; this will help to recognize potential adverse effects of these changes to the host.

Over the last decade, research into methodologies to identify skin sensitization hazards has led to the adoption of several non-animal methods as OECD guidelines. However, predictive accuracy beyond the chemical domains of the individual validation studies remains largely untested. In the present study, skin sensitization test results from in vitro and in chemico methods for 12 plant extracts and 15 polymeric materials are reported and compared to available in vivo skin sensitization data. Eight plant extracts were tested in the DPRA and h-CLAT, with the 2 out of 3 approach resulting in a balanced accuracy of 50%. The balanced accuracy for the 11 plant extracts assessed in the SENS-IS was 88%. Excluding 5 polymers inconclusive in vitro, the remainder, assessed using the 2 out of 3 approach, resulted in 63% balanced accuracy. The SENS-IS method, excluding one polymeric material due to technical inapplicability, showed 68% balanced accuracy. Although based on limited numbers, the results presented here indicate that some substance subgroups may not be in the applicability domains of the method used and careful analysis is required before positive or negative results can be accepted.

There is a need for paradigm change in the methodology employed for toxicological testing and assessment. It could be said that this change is well on its way, through an evolutionary progress analogous to that of natural selection. Darwin’s Theory of Evolution has defined the idea of evolution and descendancy since the last third of the 19th century. Increasingly, this concept of ‘evolution’ is being applied beyond the field of biology. This Comment article discusses the progress of toxicological testing in the context of ‘evolutionary pressure’ and deliberates how this process can help foster the development, implementation and acceptance of mechanistic and human-relevant methods in this field. By comparing the current regulatory landscape in toxicity testing and assessment to specific elements in Charles Darwin’s evolutionary theory, we aim to better understand the needs and requirements for the future.

Xenobiotica-metabolizing enzyme (XME) induction is a relevant biological/biochemical process vital to understanding the toxicological profile of xenobiotics. Early recognition of XME induction potential of compounds under development is therefore important, yet its determination by traditional XME activity measurements is time consuming and cost intensive. A proof-of-principle study was therefore designed due to the advent of faster and less cost-intensive methods for determination of enzyme protein and transcript levels to determine whether two such methods may substitute for traditional measurement of XME activity determinations. The results of the study show that determination of enzyme protein levels by peptide group-specific immunoaffinity enrichment/MS and/or determination of gene expression by NanoString nCounter may serve as substitutes for traditional evaluation methodology and/or as an early predictor of potential changes in liver enzymes. In this study, changes of XME activity by the known standard XME inducers phenobarbital, beta-naphthoflavone and Aroclor 1254 were demonstrated by these two methods. To investigate the applicability of these methods to demonstrate XME-inducing activity of an unknown, TS was also examined and found to be an XME inducer. More specifically, TS was found to be a phenobarbital-type inducer (likely mediated by CAR rather than PXR as nuclear receptor), but not due to Ah receptor-mediated or antioxidant response element-mediated beta-naphthoflavone-type induction. The results for TS were confirmed via enzymatic activity measurements. The results of the present study demonstrate the potential applicability of NanoString nCounter mRNA quantitation and peptide group-specific immunoaffinity enrichment/MS protein quantitation for predicting compounds under development to be inducers of liver XME activity.

No detailed information on in vivo biokinetics of CeO2 nanoparticles (NPs) following chronic low-dose inhalation is available. The CeO2 burden for lung, lung-associated lymph nodes, and major non-pulmonary organs, blood, and feces, was determined in a chronic whole-body inhalation study in female Wistar rats undertaken according to OECD TG453 (6 h per day for 5 days per week for a 104 weeks with the following concentrations: 0, 0.1, 0.3, 1.0, and 3.0 mg/m3, animals were sacrificed after 3, 12, 24 months). Different spectroscopy methods (ICP-MS, ion-beam-microscopy) were used for the quantification of organ burden and for visualization of NP distribution patterns in tissues. After 24 months of exposure, the highest CeO2 lung burden (4.41 mg per lung) was associated with the highest aerosol concentration and was proportionally lower for the other groups in a dose-dependent manner. Imaging techniques confirmed the presence of CeO2 agglomerates of different size categories within lung tissue with a non-homogenous distribution. For the highest exposure group, after 24 months in total 1.2% of the dose retained in the lung was found in the organs and tissues analyzed in this study, excluding lymph nodes and skeleton. The CeO2 burden per tissue decreased from lungs > lymph nodes > hard bone > liver > bone marrow. For two dosage groups, the liver organ burden showed a low accumulation rate. Here, the liver can be regarded as depot, whereas kidneys, the skeleton, and bone marrow seem to be dumps due to steadily increasing NP burden over time.

Nanomaterials have outstanding and unprecedented advantageous material properties but may also cause adverse effects in humans upon exposure. Testing nanomaterials for genotoxic properties is challenging because traditional testing methods were designed for small, soluble molecules and may not be easily applicable without modifications. This review critically examines available genotoxicity tests for use with nanomaterials, including DNA damage tests such as the comet assay, gene mutation tests such as the mouse lymphoma and hprt assay, and chromosome mutation tests such as the micronucleus test and the chromosome aberration test. It presents arguments for the relative usefulness of various tests, such as preferring the micronucleus test over the chromosome aberration test for scoring chromosome mutations and preferring mammalian cell gene mutation tests because the Ames test has limited utility. Finally, it points out the open questions and further needs in adapting genotoxicity tests for nanomaterials, such as validation, reference nanomaterials, and the selection of top test concentrations, as well as the relevance and applicability of test systems and the need to define testing strategies. This article is categorized under: Toxicology and Regulatory Issues in Nanomedicine > Toxicology of Nanomaterials Toxicology and Regulatory Issues in Nanomedicine > Regulatory and Policy Issues in Nanomedicine

For hazard classifications of chemicals, continuous data from animal- or nonanimal testing methods are often dichotomized into binary positive/negative outcomes by defining classification thresholds (CT). Experimental data are, however, subject to biological and technical variability. Each test method's precision is limited resulting in uncertainty of the positive/negative outcome if the experimental result is close to the CT. Borderline ranges (BR) around the CT were suggested, which represent ranges in which the study result is ambiguous, that is, positive or negative results are equally likely. The BR reflects a method's precision uncertainty. This article explores and compares different approaches to quantify the BR. Besides using the pooled standard deviation, we determine the BR by means of the median absolute deviation (MAD), with a sequential combination of both methods, and by using nonparametric bootstrapping. Furthermore, we quantify the BR for different hazardous effects, including nonanimal tests for skin corrosion, eye irritation, skin irritation, and skin sensitization as well as for an animal test on skin sensitization (the local lymph node assay, LLNA). Additionally, for one method (direct peptide reactivity assay) the BR was determined experimentally and compared to calculated BRs. Our results demonstrate that (i) the precision of the methods is determining the size of their BRs, (ii) there is no “perfect” method to derive a BR, alas, (iii) a consensus on BR is needed to account for the limited precision of testing methods.

The ECETOC NanoApp was developed to support industry in the registration of sets of nanoforms, as well as regulators in the evaluation of these registration dossiers. The ECETOC NanoApp uses a systematic approach to create and justify sets of similar nanoforms, following the ECHA guidance in a transparent and evidence-based manner. The rational and decision rules behind the ECETOC NanoApp are described in detail in ���Janer, G., R. Landsiedel, and W. Wohlleben. 2021. [Rationale and Decision Rules Behind the ECETOC NanoApp to Support Registration of Sets of Similar Nanoforms within REACH. Nanotoxicology 15 (2): 145���122. https://doi.org/10.1080/17435390.2020.1842933]���. The decision criteria apply to human health and environmental hazards and risks. Here, we focus mostly on human health hazards; the decision rules are applied to a series of case studies, each consisting of real nanoforms: two barium sulfate nanoforms, four colloidal silica nanoforms, eight ceria nanoforms, and four copper phthalocyanine nanoforms. For each of them, we show step by step how the ECETOC NanoApp rules are applied. The cases include nanoforms that are justified as members of the same set of similar nanoforms based on sufficient similarity of their intrinsic properties (Tier 1). They also include other nanoforms with a relatively high (but insufficient) similarity of intrinsic properties; their similarity could be justified by functional properties (Tier 2). The case studies also include nanoforms that are concluded not to belong to the same set of similar nanoforms. These outcomes of the NanoApp were overall consistent (sometimes conservative) with available in vivo data. We also noted that datasets for various nanoforms were limited and use of the NanoApp may require the generation of data relevant to the decision criteria.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Here, we present a non-animal testing battery to identify PSLT (poorly soluble, low toxicity) substances based on their solubility in phagolysosomal lung fluid simulant, surface reactivity and effects on alveolar macrophages in vitro. This is exemplified by eleven organic pigments belonging to five chemical classes that cover a significant share of the European market. Three of the pigments were tested as both, nanoform and non-nanoform. The results obtained in this integrated non-animal testing battery qualified two pigments as non PSLT, one pigment as poorly soluble and eight pigments as poorly soluble and low toxicity in vitro. The low toxic potency of the eight PSLT and the one poorly soluble pigment was corroborated by short-term inhalation studies with rats. These pigments did not elicit apparent toxic effects at 10 mg/m3 (systemic and in the respiratory tract). One of the pigments, Diarylide Pigment Yellow 83 transparent, however, caused minimal infiltration of neutrophils; hence its low toxicity is ambiguous and needs further verification or falsification. The present test battery provides an opportunity to identify PSLT-properties of test substances to prioritise particles for further development. Thus, it can help to reduce animal testing and steer product development towards safe applications.

Several N-vinyl compounds are produced in high volumes and are widely employed in the production of copolymers and polymers used in chemical, pharmaceutical, cosmetic and food industry. Hence, information on their genotoxicity and carcinogenicity is requisite. This review presents hitherto available information on the carcinogenicity and genotoxicity of N-vinyl compounds as well as their metabolism potentially generating genotoxic and carcinogenic derivatives. The genotoxicity and carcinogenicity of the investigated N-vinyl compounds vary widely from no observed carcinogenicity tested in lifetime bioassays in two rodent species (up to very high doses) to carcinogenicity in rats at very low doses in the absence of apparent genotoxicity. Despite of the presence of the vinyl group potentially metabolized to an epoxide followed by covalent binding to DNA, genotoxicity was observed for only one of the considered N-vinyl compounds, N-vinyl carbazole. Carcinogenicity was investigated only for two, of which one, N-vinyl pyrrolidone was carcinogenic (but not genotoxic) and ranitidine was neither carcinogenic nor genotoxic. As far as investigated, neither a metabolically formed epoxide nor a therefrom derived diol has been reported for any of the considered N-vinyl compounds. It is concluded that the information collected in this review will further the understanding of the carcinogenic potentials of N-vinyl compounds and may eventually allow approaching their prediction and prevention. A suggestion how to prevent genotoxicity in designing of N-vinyl compounds is presented. However, the available information is scarce and further research especially on the metabolism of N-vinyl compounds is highly desirable.

The availability of reference data is a key requirement for the development of new approach methods (NAM), i.e., in vitro, in chemico and in silico methods and integrated approaches, like defined approaches (DA), which combine these data sources. Reference data are of even greater importance for regulatory acceptance. In contrast to most other adverse effects, human skin sensitization data on many chemicals are available, next to data from animal studies, such as the local lymph node assay (LLNA). Skin sensitization NAM data can therefore be compared to different reference datasets. Recent publications and validation at the OECD focused on human and LLNA reference data. The “2 out of 3” DA (2o3 DA) is the first DA for skin sensitization solely based on experimental data from validated tests and was recently adopted as an OECD test guideline. Here we review the predictivity of the 2o3 DA on multiple human and LLNA reference datasets. Concomitantly, we compare the predictivity of the LLNA for human data within the same datasets. Comparing predictivity of methods not only bilaterally (NAM or DA vs. animal method) but including human data in a triangle “NAM data – animal data – human data” offers a comprehensive assessment of the NAM’s and DA’s predictivity. In all these assessments, the 2o3 DA was superior to the LLNA in predicting human skin sensitization hazard. This highlights the importance of a holistic view of reference data instead of limiting validation of NAMs and DAs to data from a single animal test only.

N-vinyl pyrrolidone (NVP) is produced up to several thousand tons per year as starting material for the production of polymers to be used in pharmaceutics, cosmetics and food technology. Upon inhalation NVP was carcinogenic in the rat, liver tumor formation is starting already at the rather low concentration of 5 ppm. Hence, differentiation whether NVP is a genotoxic carcinogen (presumed to generally have no dose threshold for the carcinogenic activity) or a non-genotoxic carcinogen (with a potentially definable threshold) is highly important. In the present study, therefore, the existing genotoxicity investigations on NVP (all showing consistently negative results) were extended and complemented with investigations on possible alternative mechanisms, which also all proved negative. All tests were performed in the same species (rat) using the same route of exposure (inhalation) and the same doses of NVP (5, 10 and 20 ppm) as had been used in the positive carcinogenicity test. Specifically, the tests included an ex vivo Comet assay (so far not available) and an ex vivo micronucleus test (in contrast to the already available micronucleus test in mice here in the same species and by the same route of application as in the bioassay which had shown the carcinogenicity), tests on oxidative stress (non-protein-bound sulfhydryls and glutathione recycling test), mechanisms mediated by hepatic receptors, the activation of which had been shown earlier to lead to carcinogenicity in some instances (Ah receptor, CAR, PXR, PPARα). No indications were obtained for any of the investigated mechanisms to be responsible for or to contribute to the observed carcinogenicity of NVP. The most important of these exclusions is genotoxicity. Thus, NVP can rightfully be regarded and treated as a non-genotoxic carcinogen and threshold approaches to the assessment of this chemical are supported. However, the mechanism underlying the carcinogenicity of NVP in rats remains unclear.

Different nanoforms (NF) of the same substance each need to be registered under REACH, but similarities in physiological interaction -among them biodissolution- can justify read-across within a group of NFs, thereby reducing the need to perform animal studies. Here we focused on the endpoint of inhalation toxicity and explored how differences in physical parameters of 17 NFs of silica, and organic and inorganic pigments impact dissolution rates, half-times, and transformation under both pH 7.4 lung lining conditions and pH 4.5 lysosomal conditions. We benchmarked our observations against well-known TiO2, BaSO4 and ZnO nanomaterials, representing very slow, partial and quick dissolution respectively. By automated image evaluation, structural transformations were observed for dissolution rates in the order of 0.1 to 10 ng/cm2/h, but did not provide additional decision criteria on the similarity of NFs. Dissolution half-times spanned nearly five orders of magnitude, mostly dictated by the substance and simulant fluid, but modulated up to ten-fold by the subtle differences between NFs. Physiological time scales and benchmark materials help to frame the biologically relevant range, proposed as 1 h to 1 y. NFs of ZnO, Ag, SiO2, BaSO4 were in this range. We proposed numerical rules of pairwise similarity within a group, of which the worst case NF would be further assessed by in vivo inhalation studies. These rules divided the colloidal silica NFs into two separate candidate groups, one with Al-doping, one without. Shape or silane surface treatment were less important. The dissolution halftimes of many organic and inorganic pigment NFs were longer than the biologically relevant range, such that dissolution behavior is not an obstacle for their groupings.

Computational methods such as machine learning approaches have a strong track record of success in predicting the outcomes of in vitro assays. In contrast, their ability to predict in vivo endpoints is more limited due to the high number of parameters and processes that may influence the outcome. Recent studies have shown that the combination of chemical and biological data can yield better models for in vivo endpoints. The ChemBioSim approach presented in this work aims to enhance the performance of conformal prediction models for in vivo endpoints by combining chemical information with (predicted) bioactivity assay outcomes. Three in vivo toxicological endpoints, capturing genotoxic (MNT), hepatic (DILI), and cardiological (DICC) issues, were selected for this study due to their high relevance for the registration and authorization of new compounds. Since the sparsity of available biological assay data is challenging for predictive modeling, predicted bioactivity descriptors were introduced instead. Thus, a machine learning model for each of the 373 collected biological assays was trained and applied on the compounds of the in vivo toxicity data sets. Besides the chemical descriptors (molecular fingerprints and physicochemical properties), these predicted bioactivities served as descriptors for the models of the three in vivo endpoints. For this study, a workflow based on a conformal prediction framework (a method for confidence estimation) built on random forest models was developed. Furthermore, the most relevant chemical and bioactivity descriptors for each in vivo endpoint were preselected with lasso models. The incorporation of bioactivity descriptors increased the mean F1 scores of the MNT model from 0.61 to 0.70 and for the DICC model from 0.72 to 0.82 while the mean efficiencies increased by roughly 0.10 for both endpoints. In contrast, for the DILI endpoint, no significant improvement in model performance was observed. Besides pure performance improvements, an analysis of the most important bioactivity features allowed detection of novel and less intuitive relationships between the predicted biological assay outcomes used as descriptors and the in vivo endpoints. This study presents how the prediction of in vivo toxicity endpoints can be improved by the incorporation of biological information-which is not necessarily captured by chemical descriptors-in an automated workflow without the need for adding experimental workload for the generation of bioactivity descriptors as predicted outcomes of bioactivity assays were utilized. All bioactivity CP models for deriving the predicted bioactivities, as well as the in vivo toxicity CP models, can be freely downloaded from https://doi.org/10.5281/zenodo.4761225.

New registration requirements for nanomaterials under REACH consider the possibility to form ‘sets of similar nanoforms’ for a joined human health and environmental hazard, exposure and risk assessment. We developed a tool to create and justify sets of similar nanoforms and to ensure that each of the nanoforms is sufficiently similar to all other nanoforms. The decision logic is following the ECHA guidance in a transparent and evidence-based manner. For each two nanoforms the properties under consideration are compared and corresponding thresholds for maximal differences are proposed. In tier1, similarity is assessed based on intrinsic properties that mostly correspond to those required for nanoform identification under REACH: composition, impurities/additives, size, crystallinity, shape and surface treatment. Moreover, potential differences in the agglomeration/aggregation state resulting from different production processes are considered. If nanoforms were not sufficiently similar based on tier1 criteria, additional data from functional assays are required in tier2. In rare cases, additional short-term in vivo rodent data could be required in a third tier. Data required by tier 2 are triggered by the intrinsic properties in the first tier that did not match the similarity criteria. Most often this will be data on dissolution and surface reactivity followed by in vitro toxicity, dispersion stability, dustiness. Out of several nanoforms given by the user, the tool concludes which nanoforms could be justified to be in the same set and which nanoforms are outside. It defines the boundaries of sets of similar nanoforms and generates a justification for the REACH registration.

In regulatory toxicology, in vivo studies are still prevailing, and human-derived in vitro models are mostly used in testing for local toxicity to the skin and the eyes. A single in vitro model may be limited to address one or few molecular or cellular events leading to adverse outcomes. Hence, in many instances their regulatory use involves the combination of several in vitro models to assess the hazard potential of test substance. A so-called defined approach combines different testing methods and a 'data interpretation procedure' to obtain a comprehensive overall assessment which is used for the regulatory hazard classification of the test substance.Validation is a prerequisite of regulatory acceptance of new testing methods: This chapter provides an overview of the method development from an experimental method to a test guideline via application of GIVIMP (good in vitro method practice), standardization, validation to the regulatory adoption as an OECD test guidelines. Quandaries associated with the validation towards reference data from in vivo animal studies with limited accuracy and limited human relevance are discussed, as well as uncertainty and limitations arising from restricted applicability and technical and biological variance of the in vitro methods.This chapter provides an overview of human-derived in vitro models currently adopted as OECD test guidelines: From the first skin corrosion tests utilizing reconstructed human epidermis models (RhE), to models to test for skin irritation, phototoxicity, eye irritation, and skin sensitization. The latter is using a battery of different methods and defined approaches which are still under discussion for their regulatory adoption. They will be a vanguard of future applications of human-derived models in regulatory toxicology. RhEs for testing of genotoxicity and of dermal penetration and absorption, have been developed, underwent validation studies and may soon be adopted for regulatory use; these are included in this chapter.

Dose-response by

While the skin sensitization hazard of substances can be identified using non-animal methods, the classification of potency into UN GHS sub-categories 1A and 1B remains challenging. The kinetic direct peptide reactivity assay (kDPRA) is a modification of the DPRA wherein the reaction kinetics of a test substance towards a synthetic cysteine-containing peptide are evaluated. For this purpose, several concentrations of the test substance are incubated with the synthetic peptide for several incubation times. The reaction is stopped by addition of monobromobimane, which forms a fluorescent complex with the free cysteine of the model peptide. The relative remaining non-depleted amount of peptide is determined. Kinetic rate constants are derived from the depletion vs concentration and time matrix and used to distinguish between UN GHS sub-category 1A sensitizers and test substances in sub-category 1B/not classified test substances. In this study, we present a ring trial of the kDPRA with 24 blind-coded test substances in seven laboratories. The intra- and inter-laboratory reproducibility were 96% and 88%, respectively (both for differentiating GHS Cat 1A sensitizers from GHS Cat 1B/not classified). Following an independent peer review, the kDPRA was considered to be acceptable for the identification of GHS Cat 1A skin sensitizers. Besides GHS Cat 1A identification, the kDPRA can be used as part of a defined approach(es) with a quantitative data integration procedure for skin sensitization potency assessment. For this aim, next to reproducibility of classification, the quantitative reproducibility and variability of the rate constants were quantified in this study.

Following inhalation and deposition in the alveolar region at sufficient dose, biopersistent (nano)materials generally provoke pulmonary inflammation. Alveolar macrophages (AMs) are mediators of pulmonary immune responses and were broadly categorized in pro-inflammatory M1 and anti-inflammatory M2 macrophages. This study aimed at identifying AM phenotype as M1 or M2 upon short-term inhalation exposure to different (nano)materials followed by a postexposure period. Phenotyping of AM was retrospectively performed using immunohistochemistry. M1 (CD68+iNOS+) and M2 (CD68+CD206+and CD68+ArgI+) AMs were characterized in formalin-fixed, paraffin-embedded lung tissue of rats exposed for 6 hours/day for 5 days to air, 100 mg/m3nano-TiO2, 25 mg/m3nano-CeO2, 32 mg/m3multiwalled carbon nanotubes, or 100 mg/m3micron-sized quartz. During acute inflammation, relative numbers of M1 AMs were markedly increased, whereas relative numbers of M2 were generally decreased compared to control. Following an exposure-free period, changes in iNOS or CD206 expression correlated with persistence, regression, or progression of inflammation, suggesting a role of M1/M2 AMs in the pathogenesis of pulmonary inflammation. However, no clear correlation of AM subpopulations with qualitatively distinct histopathological findings caused by different (nano)materials was found. A more detailed understanding of the processes underlaying these morphological changes is needed to identify biomarkers for different histopathological outcomes.

Disturbance of the thyroid hormone homeostasis has been associated with adverse health effects such as goiters and impaired mental development in humans and thyroid tumors in rats. In vitro and in silico methods for predicting the effects of small molecules on thyroid hormone homeostasis are currently being explored as alternatives to animal experiments, but are still in an early stage of development. The aim of this work was the development of a battery of in silico models for a set of targets involved in molecular initiating events of thyroid hormone homeostasis: deiodinases 1, 2, and 3, thyroid peroxidase (TPO), thyroid hormone receptor (TR), sodium/iodide symporter, thyrotropin-releasing hormone receptor, and thyroid-stimulating hormone receptor. The training data sets were compiled from the ToxCast database and related scientific literature. Classical statistical approaches as well as several machine learning methods (including random forest, support vector machine, and neural networks) were explored in combination with three data balancing techniques. The models were trained on molecular descriptors and fingerprints and evaluated on holdout data. Furthermore, multi-task neural networks combining several end points were investigated as a possible way to improve the performance of models for which the experimental data available for model training are limited. Classifiers for TPO and TR performed particularly well, with F1 scores of 0.83 and 0.81 on the holdout data set, respectively. Models for the other studied targets yielded F1 scores of up to 0.77. An in-depth analysis of the reliability of predictions was performed for the most relevant models. All data sets used in this work for model development and validation are available in the Supporting Information.

Several in vitro OECD test guidelines address key events 1-3 of the adverse outcome pathway for skin sensitization, but none are validated for sensitizer potency assessment. The reaction of sensitizing molecules with skin proteins is the molecular initiating event and appears to be rate-limiting, as chemical reactivity strongly correlates with sensitizer potency. The kinetic direct peptide reactivity assay (kDPRA), a modification of the DPRA (OECD TG 442C), allows derivation of rate constants of the depletion of the cysteine-containing model peptide upon reaction with the test item. Its reproducibility was demonstrated in an inter-laboratory study. Here, we present a database of rate constants, expressed as log kmax, for 180 chemicals to define the prediction threshold to identify strong sensitizers (classified as GHS 1A). A threshold of log kmax -2 offers a balanced accuracy of 85% for predicting GHS 1A sensitizers according to the local lymph node assay. The kDPRA is proposed as a stand-alone assay for identification of GHS 1A sensitizers among chemicals identified as sensitizers by other tests or defined approaches. It may also be used for the prediction of sensitizer potency on a continuous scale, ideally in combination with continuous parameters from other in vitro assays. We show how the rate constant could be combined with read-outs of other in vitro assays in a defined approach. A decision model based on log kmax alone has, however, a high predictivity and can be used as stand-alone model for identification of GHS 1A sensitizers among chemicals predicted as sensitizers.

In regulatory toxicology, in vivo studies are still prevailing, and human-derived in vitro models are mostly used in testing for local toxicity to the skin and the eyes. A single in vitro model may be limited to address one or few molecular or cellular events leading to adverse outcomes. Hence, in many instances their regulatory use involves the combination of several in vitro models to assess the hazard potential of test substance. A so-called defined approach combines different testing methods and a 'data interpretation procedure' to obtain a comprehensive overall assessment which is used for the regulatory hazard classification of the test substance.Validation is a prerequisite of regulatory acceptance of new testing methods: This chapter provides an overview of the method development from an experimental method to a test guideline via application of GIVIMP (good in vitro method practice), standardization, validation to the regulatory adoption as an OECD test guidelines. Quandaries associated with the validation towards reference data from in vivo animal studies with limited accuracy and limited human relevance are discussed, as well as uncertainty and limitations arising from restricted applicability and technical and biological variance of the in vitro methods.This chapter provides an overview of human-derived in vitro models currently adopted as OECD test guidelines: From the first skin corrosion tests utilizing reconstructed human epidermis models (RhE), to models to test for skin irritation, phototoxicity, eye irritation, and skin sensitization. The latter is using a battery of different methods and defined approaches which are still under discussion for their regulatory adoption. They will be a vanguard of future applications of human-derived models in regulatory toxicology. RhEs for testing of genotoxicity and of dermal penetration and absorption, have been developed, underwent validation studies and may soon be adopted for regulatory use; these are included in this chapter.

Numerous recent reviews have highlighted the urgent need for methods to determine the biodissolution of nanomaterials in relevant lung fluids, and to validate the results against the bioprocessing in vivo. Moreover, it is largely unknown to what extent (nano)forms of a substance that differ in size, shape, or coating also differ in biodissolution. Here we apply a previously optimized abiotic flow-through method to 24 (nano)forms of 6 substances and compare the results with alveolar macrophage-assisted biodissolution of a subset of these nanomaterials in vitro and short-term inhalation results in vivo. As a main result we found that the results obtained with the flow-through method for the lung were consistent to the results of in vivo studies and were not improved by measuring alveolar macrophage-assisted biodissolution for up to 48 h. Based on selected benchmark materials we propose four groups of materials according to quantitative biodissolution rates (1 ng/cm2/h to 100 ng/cm2/h cutoffs) and qualitative transformation parameters, as detected by TEM analysis. These groups were also reflected by different lung clearance rates, as previously determined in short term inhalation studies. Biodissolution was similar within substance (nano)forms of Fe2O3, SiO2, CeO2, ZnO, though slightly varied upon surface area/coating. But the difference of biodissolution between the substances was in some cases >1000-fold. Among the Cu-containing materials, the behavior of the two CuPhthalocyanin nanoforms was similar with each other, but completely different than the dissolution and transformation of Cu salts. Different production routes and/or surface coatings significantly modulated biodissolution, whereas effects of shape or size were limited. In summary, we refined a protocol for the abiotic determination of biodissolution along with an integrated assessment of nanomaterial transformation. The protocol is suggested as tier 2 methodology for grouping and read-across purposes.

Studies on the metabolic fate of medical drugs, skin care products, cosmetics and other chemicals intentionally or accidently applied to the human skin have become increasingly important in order to ascertain pharmacological effectiveness and to avoid toxicities. The use of freshly excised human skin for experimental investigations meets with ethical and practical limitations. Hence information on xenobiotic-metabolizing enzymes (XME) in the experimental systems available for pertinent studies compared with native human skin has become crucial. This review collects available information of which-taken with great caution because of the still very limited data-the most salient points are: in the skin of all animal species and skin-derived in vitro systems considered in this review cytochrome P450 (CYP)-dependent monooxygenase activities (largely responsible for initiating xenobiotica metabolism in the organ which provides most of the xenobiotica metabolism of the mammalian organism, the liver) are very low to undetectable. Quite likely other oxidative enzymes [e.g. flavin monooxygenase, COX (cooxidation by prostaglandin synthase)] will turn out to be much more important for the oxidative xenobiotic metabolism in the skin. Moreover, conjugating enzyme activities such as glutathione transferases and glucuronosyltransferases are much higher than the oxidative CYP activities. Since these conjugating enzymes are predominantly detoxifying, the skin appears to be predominantly protected against CYP-generated reactive metabolites. The following recommendations for the use of experimental animal species or human skin in vitro models may tentatively be derived from the information available to date: for dermal absorption and for skin irritation esterase activity is of special importance which in pig skin, some human cell lines and reconstructed skin models appears reasonably close to native human skin. With respect to genotoxicity and sensitization reactive-metabolite-reducing XME in primary human keratinocytes and several reconstructed human skin models appear reasonably close to human skin. For a more detailed delineation and discussion of the severe limitations see the Conclusions section in the end of this review.

In vivo acute systemic testing is a regulatory requirement for agrochemical formulations. GHS specifies an alternative computational approach (GHS additivity formula) for calculating the acute toxicity of mixtures. We collected acute systemic toxicity data from formulations that contained one of several acutely-toxic active ingredients. The resulting acute data set includes 210 formulations tested for oral toxicity, 128 formulations tested for inhalation toxicity and 31 formulations tested for dermal toxicity. The GHS additivity formula was applied to each of these formulations and compared with the experimental in vivo result. In the acute oral assay, the GHS additivity formula misclassified 110 formulations using the GHS classification criteria (48% accuracy) and 119 formulations using the USEPA classification criteria (43% accuracy). With acute inhalation, the GHS additivity formula misclassified 50 formulations using the GHS classification criteria (61% accuracy) and 34 formulations using the USEPA classification criteria (73% accuracy). For acute dermal toxicity, the GHS additivity formula misclassified 16 formulations using the GHS classification criteria (48% accuracy) and 20 formulations using the USEPA classification criteria (36% accuracy). This data indicates the acute systemic toxicity of many formulations is not the sum of the ingredients' toxicity (additivity); but rather, ingredients in a formulation can interact to result in lower or higher toxicity than predicted by the GHS additivity formula.

Different in vitro approaches exist to identify agonistic or antagonistic activity of chemical substances concerning nuclear receptors, since adverse effects in vivo can be the consequence. The recruitment of coregulators by nuclear receptors is a key step in the ligand-induced transcription of controlled genes. Therefore, the microarray assay for real-time coregulator-nuclear receptor interaction (MARCoNI) was tested in combination with a reporter cell assay as a screening tool in toxicology.