KnowTox: pipeline and case study for confident prediction of potential toxic effects of compounds in early phases of development

Risk assessment of newly synthesised chemicals is a prerequisite for regulatory approval. In this context, in silico methods have great potential to reduce time, cost, and ultimately animal testing as they make use of the ever-growing amount of available toxicity data. Here, KnowTox is presented, a novel pipeline that combines three different in silico toxicology approaches to allow for confident prediction of potentially toxic effects of query compounds, i.e. machine learning models for 88 endpoints, alerts for 919 toxic substructures, and computational support for read-across. It is mainly based on the ToxCast dataset, containing after preprocessing a sparse matrix of 7912 compounds tested against 985 endpoints. When applying machine learning models, applicability and reliability of predictions for new chemicals are of utmost importance. Therefore, first, the conformal prediction technique was deployed, comprising an additional calibration step and per definition creating internally valid predictors at a given significance level. Second, to further improve validity and information efficiency, two adaptations are suggested, exemplified at the androgen receptor antagonism endpoint. An absolute increase in validity of 23% on the in-house dataset of 534 compounds could be achieved by introducing KNNRegressor normalisation. This increase in validity comes at the cost of efficiency, which could again be improved by 20% for the initial ToxCast model by balancing the dataset during model training. Finally, the value of the developed pipeline for risk assessment is discussed using two in-house triazole molecules. Compared to a single toxicity prediction method, complementing the outputs of different approaches can have a higher impact on guiding toxicity testing and de-selecting most likely harmful development-candidate compounds early in the development process

The Embryonic Stem Cell Test as Tool to Assess Structure-Dependent Teratogenicity: The Case of Valproic Acid

Teratogenicity can be predicted in vitro using the embryonic stem cell test (EST). The EST, which is based on the morphometric measurement of cardiomyocyte differentiation and cytotoxicity parameters, represents a scientifically validated method for the detection and classification of chemicals according to their teratogenic potency. Furthermore, an abbreviated protocol applying flow cytometry of intracellular marker proteins to determine differentiation into the cardiomyocyte lineage is available. Although valproic acid (VPA) is in worldwide clinical use as antiepileptic drug, it exhibits two severe side effects, i.e., teratogenicity and hepatotoxicity. These limitations have led to extensive research into derivatives of VPA. Here we chose VPA as model compound to test the applicability domain and to further evaluate the reliability of the EST. To this end, we study six closely related congeners of VPA and demonstrate that both the standard and the molecular flow cytometry-based EST are well suited to indicate differences in the teratogenic potency among VPA analogs that differ only in chirality or side chain length. Our data show that identical results can be obtained by using the standard EST or a shortened protocol based on flow cytometry of intracellular marker proteins. Both in vitro protocols enable to reliably determine differentiation of murine stem cells toward the cardiomyocyte lineage and to assess its chemical-mediated inhibition

Safety evaluation of a β-mannanase enzyme preparation produced with Thermothelomyces thermophilus expressing a protein-engineered β-mannanase gene.

Mannanase 19287 enzyme is an engineered β-mannanase that can be added to diets for animals raised for human consumption to hydrolyze β-mannans. Established toxicological analyses were conducted with the enzyme preparation to ensure the safety of this product for the intended use. The mannanase 19287 preparation was produced with Thermothelomyces thermophilus strain DSM 33149. In vitro toxicity studies presented here used dosages of the mannanase 19287 test articles up to 5000 μg/plate. For in vivo toxicity studies in Wistar rats, test articles were administered at 5.1 mg/L for inhalation toxicity and up to 15,000 mg/kg rat feed for oral toxicity, based on the Total Organic Solids (TOS) content in each test article. No treatment related adverse effects were reported in any study. The No Observed Adverse Effect Levels in the high dose group of the subchronic oral toxicity study were calculated as 1117-1298 mg TOS/kg bw/day in rats. Comparing these values to an Estimated Daily Intake for poultry demonstrated safety factors larger than 5000. Our results confirm that T. thermophilus fulfills the recognized safety criteria for the manufacture of food enzyme preparations and represent the first peer-reviewed safety evaluation of an enzyme preparation by T. thermophilus. The results of the toxicity studies presented herein attest to the safety of the mannanase 19287 enzyme for its intended use

Prospects and challenges of multi-omics data integration in toxicology

Exposure of cells or organisms to chemicals can trigger a series of effects at the regulatory pathway level, which involve changes of levels, interactions, and feedback loops of biomolecules of different types. A single-omics technique, e.g., transcriptomics, will detect biomolecules of one type and thus can only capture changes in a small subset of the biological cascade. Therefore, although applying single-omics analyses can lead to the identification of biomarkers for certain exposures, they cannot provide a systemic understanding of toxicity pathways or adverse outcome pathways. Integration of multiple omics data sets promises a substantial improvement in detecting this pathway response to a toxicant, by an increase of information as such and especially by a systemic understanding. Here, we report the findings of a thorough evaluation of the prospects and challenges of multi-omics data integration in toxicological research. We review the availability of such data, discuss options for experimental design, evaluate methods for integration and analysis of multi-omics data, discuss best practices, and identify knowledge gaps. Re-analyzing published data, we demonstrate that multi-omics data integration can considerably improve the confidence in detecting a pathway response. Finally, we argue that more data need to be generated from studies with a multi-omics-focused design, to define which omics layers contribute most to the identification of a pathway response to a toxicant

Guidance on classification for reproductive toxicity under the globally harmonized system of classification and labelling of chemicals (GHS)

With a wider remit, the United Nations formulated a classification and labelling system for universal application, the Globally Harmonized System of Classification and Labelling of Chemicals (GHS). The GHS was first published in 2003 (UN, 2003) and subsequently updated on a biannual basis, with the most recent revision published in 2009 (UN, 2009a). It was enacted into the European legislative framework as Regulation 1272/2008 (EC, 2008). The supplementary guidance text of the GHS explains the application of the classification criteria (Box 1). It uses more advisory, less obligatory, language than the equivalent EU text (e.g. “should” vs. “shall”), but overall the differences between the two are minor and are noted in the footnotes to Box 1. This review offers guidance for the classification of substances for toxicity to reproduction according to the GHS; as a whole it applies equally to both regulatory frameworksJRC.I.5-Systems Toxicolog

Applying 'omics technologies in chemicals risk assessment: Report of an ECETOC workshop

Prevailing knowledge gaps in linking specific molecular changes to apical outcomes and methodological uncertainties in the generation, storage, processing, and interpretation of 'omics data limit the application of 'omics technologies in regulatory toxicology. Against this background, the European Centre for Ecotoxicology and Toxicology of Chemicals (ECETOC) convened a workshop Applying 'omics technologies in chemicals risk assessment that is reported herein. Ahead of the workshop, multi-expert teams drafted frameworks on best practices for (i) a Good-Laboratory Practice-like context for collecting, storing and curating 'omics data; (ii) the processing of 'omics data; and (iii) weight-of-evidence approaches for integrating 'omics data. The workshop participants confirmed the relevance of these Frameworks to facilitate the regulatory applicability and use of 'omics data, and the workshop discussions provided input for their further elaboration. Additionally, the key objective (iv) to establish approaches to connect 'omics perturbations to phenotypic alterations was addressed. Generally, it was considered promising to strive to link gene expression changes and pathway perturbations to the phenotype by mapping them to specific adverse outcome pathways. While further work is necessary before gene expression changes can be used to establish safe levels of substance exposure, the ECETOC workshop provided important incentives towards achieving this goal