Correction: Peters et al. Benchmarking the ACEnano Toolbox for Characterisation of Nanoparticle Size and Concentration by Interlaboratory Comparison. Molecules 2021, 26, 5315.

Due to miscommunication a number of potential co-authors were not listed in the original publication [...].

Semi-automated approach for generation of biological networks on drug-induced cholestasis, steatosis, hepatitis, and cirrhosis.

Drug-induced liver injury (DILI) is one of the leading reasons for discontinuation of a new drug development project. Diverse machine learning or deep learning models have been developed to predict DILI. However, these models have not provided an adequate understanding of the mechanisms leading to DILI. The development of safer drugs requires novel computational approaches that enable the prompt understanding of the mechanism of DILI. In this study, the mechanisms leading to the development of cholestasis, steatosis, hepatitis, and cirrhosis were explored using a semi-automated approach for data gathering and associations. Diverse data from ToxCast, Comparative Toxicogenomic Database (CTD), Reactome, and Open TG-GATEs on reference molecules leading to the development of the respective diseases were extracted. The data were used to create biological networks of the four diseases. As expected, the four networks had several common pathways, and a joint DILI network was assembled. Such biological networks could be used in drug discovery to identify possible molecules of concern as they provide a better understanding of the disease-specific key events. The events can be target-tested to provide indications for potential DILI effects. Supplementary Information: The online version contains supplementary material available at 10.1007/s43188-022-00124-6.

How to Foster 'New Approach Methodology' Toxicologists.

The need to reduce, refine and replace animal experimentation has led to a boom in the establishment of new approach methodologies (NAMs). This promising trend brings the hope that the replacement of animals by using NAMs will become increasingly accepted by regulators, included in legislation, and consequently more-often implemented by industry. The majority of NAMs, however, are still not very well understood, either due to the complexity of the applied approach or the data analysis workflow. A potential solution to this problem is the provision of better educational resources to scientists new to the area - showcasing the added value of NAMs and outlining various ways of overcoming issues associated with knowledge gaps. In this paper, the educational exchange between four institutions - namely, two universities and two SMEs - via a series of video training sessions, is described. The goal of this exchange was to showcase an exemplary event to help introduce scientists to non-animal approaches, and to actively support the development of resources enabling the use of alternatives to laboratory animals.

An in vitro strategy using multiple human induced pluripotent stem cell-derived models to assess the toxicity of chemicals: A case study on paraquat.

Most OECD guidelines for chemical risk assessment include tests performed on animals, raising financial, ethical and scientific concerns. Thus, the development of human-based models for toxicity testing is highly encouraged. Here, we propose an in vitro multi-organ strategy to assess the toxicity of chemicals. Human induced pluripotent stem cells (hiPSCs)-derived models of the brain, blood-brain barrier, kidney, liver and vasculature were generated and exposed to paraquat (PQ), a widely employed herbicide with known toxic effects in kidneys and brain. The models showed differential cytotoxic sensitivity to PQ after acute exposure. TempO-Seq analysis with a set of 3565 probes revealed the deregulation of oxidative stress, unfolded protein response and estrogen receptor-mediated signaling pathways, in line with the existing knowledge on PQ mechanisms of action. The main advantages of this strategy are to assess chemical toxicity on multiple tissues/organs in parallel, exclusively in human cells, eliminating the interspecies bias, allowing a better evaluation of the differential sensitivity of the models representing the diverse organs, and increasing the chance to identify toxic compounds. Furthermore, although we focused on the mechanisms of action of PQ shared by the different models, this strategy would also allow for organ-specific toxicity testing, by including more cell type-specific probes for TempO-Seq analyses. In conclusion, we believe this strategy will participate in the further improvement of chemical risk assessment for human health.

Benchmarking the ACEnano Toolbox for Characterisation of Nanoparticle Size and Concentration by Interlaboratory Comparisons.

ACEnano is an EU-funded project which aims at developing, optimising and validating methods for the detection and characterisation of nanomaterials (NMs) in increasingly complex matrices to improve confidence in the results and support their use in regulation. Within this project, several interlaboratory comparisons (ILCs) for the determination of particle size and concentration have been organised to benchmark existing analytical methods. In this paper the results of a number of these ILCs for the characterisation of NMs are presented and discussed. The results of the analyses of pristine well-defined particles such as 60 nm Au NMs in a simple aqueous suspension showed that laboratories are well capable of determining the sizes of these particles. The analysis of particles in complex matrices or formulations such as consumer products resulted in larger variations in particle sizes within technologies and clear differences in capability between techniques. Sunscreen lotion sample analysis by laboratories using spICP-MS and TEM/SEM identified and confirmed the TiO2 particles as being nanoscale and compliant with the EU definition of an NM for regulatory purposes. In a toothpaste sample orthogonal results by PTA, spICP-MS and TEM/SEM agreed and stated the TiO2 particles as not fitting the EU definition of an NM. In general, from the results of these ILCs we conclude that laboratories are well capable of determining particle sizes of NM, even in fairly complex formulations.

Temporal transcriptomic alterations of cadmium exposed human iPSC-derived renal proximal tubule-like cells.

Cadmium is a well-studied environmental pollutant where the kidney and particularly the proximal tubule cells are especially sensitive as they are exposed to higher concentrations of cadmium than other tissues. Here we investigated the temporal transcriptomic alterations (TempO-Seq) of human induced pluripotent stem cell (iPSC)-derived renal proximal tubule-like (PTL) cells exposed to 5 µM cadmium chloride for 1, 2, 4, 8, 12, 16, 20, 24, 72 and 168 h. There was an early activation (within 4 h) of the metal and oxidative stress responses (metal-responsive transcription factor-1 (MTF1) and nuclear factor erythroid-2-related factor 2 (Nrf2) genes). The Nrf2 response returned to baseline within 24 h. The Activator Protein 1 (AP-1) regulated genes HSPA6 and FOSL-1 followed the Nrf2 time course. While the MTF1 genes also spiked at 4 h, they remained strongly elevated over the entire exposure period. The data and cell culture model utilised will be useful in further research aimed at the refinement of safe human exposure limits for cadmium, other metals and their mixtures.

Skin sensitization in silico protocol.

The assessment of skin sensitization has evolved over the past few years to include in vitro assessments of key events along the adverse outcome pathway and opportunistically capitalize on the strengths of in silico methods to support a weight of evidence assessment without conducting a test in animals. While in silico methods vary greatly in their purpose and format; there is a need to standardize the underlying principles on which such models are developed and to make transparent the implications for the uncertainty in the overall assessment. In this contribution, the relationship between skin sensitization relevant effects, mechanisms, and endpoints are built into a hazard assessment framework. Based on the relevance of the mechanisms and effects as well as the strengths and limitations of the experimental systems used to identify them, rules and principles are defined for deriving skin sensitization in silico assessments. Further, the assignments of reliability and confidence scores that reflect the overall strength of the assessment are discussed. This skin sensitization protocol supports the implementation and acceptance of in silico approaches for the prediction of skin sensitization.

A semi-automated workflow for adverse outcome pathway hypothesis generation: The use case of non-genotoxic induced hepatocellular carcinoma.

The utility of the Adverse Outcome Pathway (AOP) concept has been largely recognized by scientists, however, the AOP generation is still mainly done manually by screening through evidence and extracting probable associations. To accelerate this process and increase the reliability, we have developed an semi-automated workflow for AOP hypothesis generation. In brief, association mining methods were applied to high-throughput screening, gene expression, in vivo and disease data present in ToxCast and Comparative Toxicogenomics Database. This was supplemented by pathway mapping using Reactome to fill in gaps and identify events occurring at the cellular/tissue levels. Furthermore, in vivo data from TG-Gates was integrated to finally derive a gene, pathway, biochemical, histopathological and disease network from which specific disease sub-networks can be queried. To test the workflow, non-genotoxic-induced hepatocellular carcinoma (HCC) was selected as a case study. The implementation resulted in the identification of several non-genotoxic-specific HCC-connected genes belonging to cell proliferation, endoplasmic reticulum stress and early apoptosis. Biochemical findings revealed non-genotoxic-specific alkaline phosphatase increase. The explored non-genotoxic-specific histopathology was associated with early stages of hepatic steatosis, transforming into cirrhosis. This work illustrates the utility of computationally predicted constructs in supporting development by using pre-existing knowledge in a fast and unbiased manner.

Erratum to Template for the description of cell-based toxicological test methods to allow evaluation and regulatory use of the data.

In this manuscript, which appeared in ALTEX (2019), 36(4), 682- 699, doi:10.14573/altex.1909271 , the affiliation of Hennicke Kamp should be Experimental Toxicology and Ecology, BASF SE, Ludwigshafen, Germany. Further, the reference to an article by Bal-Price et al. (2015) should have the following doi:10.1007/s00204-015-1464-2 .

Template for the description of cell-based toxicological test methods to allow evaluation and regulatory use of the data.

Only few cell-based test methods are described by Organisation for Economic Co-operation and Development (OECD) test guidelines or other regulatory references (e.g., the European Pharmacopoeia). The majority of toxicity tests still falls into the category of non-guideline methods. Data from these tests may nevertheless be used to support regulatory decisions or to guide strategies to assess compounds (e.g., drugs, agrochemicals) during research and development if they fulfill basic requirements concerning their relevance, reproducibility and predictivity. Only a method description of sufficient clarity and detail allows interpretation and use of the data. To guide regulators faced with increasing amounts of data from non-guideline studies, the OECD formulated Guidance Document 211 (GD211) on method documentation for the purpose of safety assessment. As GD211 is targeted mainly at regulators, it leaves scientists less familiar with regulation uncertain as to what level of detail is required and how individual questions should be answered. Moreover, little attention was given to the description of the test system (i.e., cell culture) and the steps leading to it being established in the guidance. To address these issues, an annotated toxicity test method template (ToxTemp) was developed (i) to fulfill all requirements of GD211, (ii) to guide the user concerning the types of answers and detail of information required, (iii) to include acceptance criteria for test elements, and (iv) to define the cells sufficiently and transparently. The fully annotated ToxTemp is provided here, together with reference to a database containing exemplary descriptions of more than 20 cell-based tests.

Integrated analysis of in vitro data and the adverse outcome pathway framework for prioritization and regulatory applications: An exploratory case study using publicly available data on piperonyl butoxide and liver models.

The integration of existing knowledge to support the risk assessment of chemicals is an ongoing challenge for scientists, risk assessors and risk managers. In addition, European Union regulations limiting the use of new animal testing in cosmetics makes already existing information even more valuable. Applying a previous SEURAT-1 program framework to derive predictions of in vivo toxicity responses for a compound, we selected piperonyl butoxide (PBO) as a case study for identification of knowledge and methodology gaps in understanding a compound's effects on the human liver. This is investigated through integration of data from human in vitro transcriptomics studies, biological pathway analysis, chemical and disease associations, and adverse outcome pathway (AOP) information. The outcomes of the analysis are used to generate AOPs of liver-related endpoints, identifying areas of concern for risk assessors and regulators. We demonstrate that integration of data through already existing and publicly available tools can produce outcomes comparable to those that may be found through more conventional time- and resource-intensive methods. It is also expected that, with more refinement, this approach could in the future provide evidence to support chemical risk assessment, while also identifying data gaps for which additional testing may be needed.

Advanced tools for the safety assessment of nanomaterials.

Engineered nanomaterials (ENMs) have tremendous potential to produce beneficial technological impact in numerous sectors in society. Safety assessment is, of course, of paramount importance. However, the myriad variations of ENM properties makes the identification of specific features driving toxicity challenging. At the same time, reducing animal tests by introducing alternative and/or predictive in vitro and in silico methods has become a priority. It is important to embrace these new advances in the safety assessment of ENMs. Indeed, remarkable progress has been made in recent years with respect to mechanism-based hazard assessment of ENMs, including systems biology approaches as well as high-throughput screening platforms, and new tools are also emerging in risk assessment and risk management for humans and the environment across the whole life-cycle of nano-enabled products. Here, we highlight some of the key advances in the hazard and risk assessment of ENMs.

Emerging technologies for food and drug safety.

Emerging technologies are playing a major role in the generation of new approaches to assess the safety of both foods and drugs. However, the integration of emerging technologies in the regulatory decision-making process requires rigorous assessment and consensus amongst international partners and research communities. To that end, the Global Coalition for Regulatory Science Research (GCRSR) in partnership with the Brazilian Health Surveillance Agency (ANVISA) hosted the seventh Global Summit on Regulatory Science (GSRS17) in Brasilia, Brazil on September 18-20, 2017 to discuss the role of new approaches in regulatory science with a specific emphasis on applications in food and medical product safety. The global regulatory landscape concerning the application of new technologies was assessed in several countries worldwide. Challenges and issues were discussed in the context of developing an international consensus for objective criteria in the development, application and review of emerging technologies. The need for advanced approaches to allow for faster, less expensive and more predictive methodologies was elaborated. In addition, the strengths and weaknesses of each new approach was discussed. And finally, the need for standards and reproducible approaches was reviewed to enhance the application of the emerging technologies to improve food and drug safety. The overarching goal of GSRS17 was to provide a venue where regulators and researchers meet to develop collaborations addressing the most pressing scientific challenges and facilitate the adoption of novel technical innovations to advance the field of regulatory science.

In silico toxicology protocols.

The present publication surveys several applications of in silico (i.e., computational) toxicology approaches across different industries and institutions. It highlights the need to develop standardized protocols when conducting toxicity-related predictions. This contribution articulates the information needed for protocols to support in silico predictions for major toxicological endpoints of concern (e.g., genetic toxicity, carcinogenicity, acute toxicity, reproductive toxicity, developmental toxicity) across several industries and regulatory bodies. Such novel in silico toxicology (IST) protocols, when fully developed and implemented, will ensure in silico toxicological assessments are performed and evaluated in a consistent, reproducible, and well-documented manner across industries and regulatory bodies to support wider uptake and acceptance of the approaches. The development of IST protocols is an initiative developed through a collaboration among an international consortium to reflect the state-of-the-art in in silico toxicology for hazard identification and characterization. A general outline for describing the development of such protocols is included and it is based on in silico predictions and/or available experimental data for a defined series of relevant toxicological effects or mechanisms. The publication presents a novel approach for determining the reliability of in silico predictions alongside experimental data. In addition, we discuss how to determine the level of confidence in the assessment based on the relevance and reliability of the information.

Supporting evidence-based analysis for modified risk tobacco products through a toxicology data-sharing infrastructure.

The US FDA defines modified risk tobacco products (MRTPs) as products that aim to reduce harm or the risk of tobacco-related disease associated with commercially marketed tobacco products.  Establishing a product's potential as an MRTP requires scientific substantiation including toxicity studies and measures of disease risk relative to those of cigarette smoking.  Best practices encourage verification of the data from such studies through sharing and open standards. Building on the experience gained from the OpenTox project, a proof-of-concept database and website ( INTERVALS) has been developed to share results from both in vivo inhalation studies and in vitro studies conducted by Philip Morris International R&D to assess candidate MRTPs. As datasets are often generated by diverse methods and standards, they need to be traceable, curated, and the methods used well described so that knowledge can be gained using data science principles and tools. The data-management framework described here accounts for the latest standards of data sharing and research reproducibility. Curated data and methods descriptions have been prepared in ISA-Tab format and stored in a database accessible via a search portal on the INTERVALS website. The portal allows users to browse the data by study or mechanism (e.g., inflammation, oxidative stress) and obtain information relevant to study design, methods, and the most important results. Given the successful development of the initial infrastructure, the goal is to grow this initiative and establish a public repository for 21 st-century preclinical systems toxicology MRTP assessment data and results that supports open data principles.

Adverse outcome pathways: opportunities, limitations and open questions.

Adverse outcome pathways (AOPs) are a recent toxicological construct that connects, in a formalized, transparent and quality-controlled way, mechanistic information to apical endpoints for regulatory purposes. AOP links a molecular initiating event (MIE) to the adverse outcome (AO) via key events (KE), in a way specified by key event relationships (KER). Although this approach to formalize mechanistic toxicological information only started in 2010, over 200 AOPs have already been established. At this stage, new requirements arise, such as the need for harmonization and re-assessment, for continuous updating, as well as for alerting about pitfalls, misuses and limits of applicability. In this review, the history of the AOP concept and its most prominent strengths are discussed, including the advantages of a formalized approach, the systematic collection of weight of evidence, the linkage of mechanisms to apical end points, the examination of the plausibility of epidemiological data, the identification of critical knowledge gaps and the design of mechanistic test methods. To prepare the ground for a broadened and appropriate use of AOPs, some widespread misconceptions are explained. Moreover, potential weaknesses and shortcomings of the current AOP rule set are addressed (1) to facilitate the discussion on its further evolution and (2) to better define appropriate vs. less suitable application areas. Exemplary toxicological studies are presented to discuss the linearity assumptions of AOP, the management of event modifiers and compensatory mechanisms, and whether a separation of toxicodynamics from toxicokinetics including metabolism is possible in the framework of pathway plasticity. Suggestions on how to compromise between different needs of AOP stakeholders have been added. A clear definition of open questions and limitations is provided to encourage further progress in the field.

CompNanoTox2015: novel perspectives from a European conference on computational nanotoxicology on predictive nanotoxicology.

A first European Conference on Computational Nanotoxicology, CompNanoTox, was held in November 2015 in Benahavís, Spain with the objectives to disseminate and integrate results from the European modeling and database projects (NanoPUZZLES, ModENPTox, PreNanoTox, MembraneNanoPart, MODERN, eNanoMapper and EU COST TD1204 MODENA) as well as to create synergies within the European NanoSafety Cluster. This conference was supported by the COST Action TD1204 MODENA on developing computational methods for toxicological risk assessment of engineered nanoparticles and provided a unique opportunity for cross fertilization among complementary disciplines. The efforts to develop and validate computational models crucially depend on high quality experimental data and relevant assays which will be the basis to identify relevant descriptors. The ambitious overarching goal of this conference was to promote predictive nanotoxicology, which can only be achieved by a close collaboration between the computational scientists (e.g. database experts, modeling experts for structure, (eco) toxicological effects, performance and interaction of nanomaterials) and experimentalists from different areas (in particular toxicologists, biologists, chemists and material scientists, among others). The main outcome and new perspectives of this conference are summarized here.

Toward the Replacement of Animal Experiments through the Bioinformatics-driven Analysis of 'Omics' Data from Human Cell Cultures.

This paper outlines the work for which Roland Grafström and Pekka Kohonen were awarded the 2014 Lush Science Prize. The research activities of the Grafström laboratory have, for many years, covered cancer biology studies, as well as the development and application of toxicity-predictive in vitro models to determine chemical safety. Through the integration of in silico analyses of diverse types of genomics data (transcriptomic and proteomic), their efforts have proved to fit well into the recently-developed Adverse Outcome Pathway paradigm. Genomics analysis within state-of-the-art cancer biology research and Toxicology in the 21st Century concepts share many technological tools. A key category within the Three Rs paradigm is the Replacement of animals in toxicity testing with alternative methods, such as bioinformatics-driven analyses of data obtained from human cell cultures exposed to diverse toxicants. This work was recently expanded within the pan-European SEURAT-1 project (Safety Evaluation Ultimately Replacing Animal Testing), to replace repeat-dose toxicity testing with data-rich analyses of sophisticated cell culture models. The aims and objectives of the SEURAT project have been to guide the application, analysis, interpretation and storage of 'omics' technology-derived data within the service-oriented sub-project, ToxBank. Particularly addressing the Lush Science Prize focus on the relevance of toxicity pathways, a 'data warehouse' that is under continuous expansion, coupled with the development of novel data storage and management methods for toxicology, serve to address data integration across multiple 'omics' technologies. The prize winners' guiding principles and concepts for modern knowledge management of toxicological data are summarised. The translation of basic discovery results ranged from chemical-testing and material-testing data, to information relevant to human health and environmental safety.