Publications by authors named "Thomas Exner"

Modelling Data (MODA) reporting guidelines have been proposed for common terminology and for recording metadata for physics-based materials modelling and simulations in a CEN Workshop Agreement (CWA 17284:2018). Their purpose is similar to that of the Quantitative Structure-Activity Relationship (QSAR) model report form (QMRF) that aims to increase industry and regulatory confidence in QSAR models, but for a wider range of model types. Recently, the WorldFAIR project's nanomaterials case study suggested that both QMRF and MODA templates are an important means to enhance compliance of nanoinformatics models, and their underpinning datasets, with the FAIR principles (Findable, Accessible, Interoperable, Reusable).

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Cyclosporin A (CSA) is a potent immunosuppressive agent in pharmacologic studies. However, there is evidence for side effects, specifically regarding vascular dysfunction. Its mode of action inducing endothelial cell toxicity is partially unclear, and a connection with an adverse outcome pathway (AOP) is not established yet.

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Article Synopsis
  • The National Nanotechnology Initiative held a Nanoinformatics Conference in 2023, discussing collaborations between the U.S. and EU on handling nanotechnology data.
  • They talked about creating databases, their pros and cons, and how to improve standards for sharing and storing information about nano Environmental Health and Safety (nanoEHS).
  • Important topics that were missed include evaluating data usage, including community input, and integrating new data types like micro and nano plastics for better future progress.
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The increasing prevalence of endocrine-disrupting chemicals (EDCs) and their potential adverse effects on human health underscore the necessity for robust tools to assess and manage associated risks. The androgen receptor (AR) is a critical component of the endocrine system, playing a pivotal role in mediating the biological effects of androgens, which are male sex hormones. Exposure to androgen-disrupting chemicals during critical periods of development, such as fetal development or puberty, may result in adverse effects on reproductive health, including altered sexual differentiation, impaired fertility, and an increased risk of reproductive disorders.

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Knowledge of protein-ligand complexes is essential for efficient drug design. Virtual docking can bring important information on putative complexes but it is still far from being simultaneously fast and accurate. Receptors are flexible and adapt to the incoming small molecules while docking is highly sensitive to small conformational deviations.

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The EU-ToxRisk project (2016-2021) was a large European project working towards shifting toxicological testing away from animal tests, towards a toxicological assessment based on comprehensive mechanistic understanding of cause-consequence relationships of chemical adverse effects. More than 40 partners from scientific institutions, industry and regulators coordinated their work towards this goal in a six-year long programme. The breadth and variety of data and knowledge generated, presented a challenging data management landscape.

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The adoption of innovative advanced materials holds vast potential, contingent upon addressing safety and sustainability concerns. The European Commission advocates the integration of Safe and Sustainable by Design (SSbD) principles early in the innovation process to streamline market introduction and mitigate costs. Within this framework, encompassing ecological, social, and economic factors is paramount.

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Human induced pluripotent stem cells (iPSC) have the potential to produce desired target cell types in vitro and allow for the high-throughput screening of drugs/chemicals at population level thereby minimising the cost of drug discovery and drug withdrawals after clinical trials. There is a substantial need for the characterisation of the iPSC derived models to better understand and utilise them for toxicological relevant applications. In our study, iPSC (SBAD2 or SBAD3 lines obtained from StemBANCC project) were differentiated towards toxicologically relevant cell types: alveolar macrophages, brain capillary endothelial cells, brain cells, endothelial cells, hepatocytes, lung airway epithelium, monocytes, podocytes and renal proximal tubular cells.

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Background: Direct oral anticoagulants (DOACs) cause unwanted interference in various hemostasis assays, including lupus anticoagulant (LA) testing, where false positive and false negative identification may occur. DOAC Stop (DS) is an activated charcoal (AC) product used to specifically and effectively adsorb DOACs from test plasma. This process normally requires plasma treatment, centrifugation and plasma separation prior to tests, but inexperienced operators may also inadvertently transfer residual AC particles, thereby potentially adversely affecting clot detection.

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Toxicology has been an active research field for many decades, with academic, industrial and government involvement. Modern omics and computational approaches are changing the field, from merely disease-specific observational models into target-specific predictive models. Traditionally, toxicology has strong links with other fields such as biology, chemistry, pharmacology and medicine.

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Transcriptomic analysis is a powerful method in the utilization of New Approach Methods (NAMs) for identifying mechanisms of toxicity and application to hazard characterization. With this regard, mapping toxicological events to time of exposure would be helpful to characterize early events. Here, we investigated time-dependent changes in gene expression levels in iPSC-derived renal proximal tubular-like cells (PTL) treated with five diverse compounds using TempO-Seq transcriptomics with the aims to evaluate the application of PTL for toxicity prediction and to report on temporal effects for the activation of cellular stress response pathways.

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Management of nanomaterials and nanosafety data needs to operate under the FAIR (findability, accessibility, interoperability, and reusability) principles and this requires a unique, global identifier for each nanomaterial. Existing identifiers may not always be applicable or sufficient to definitively identify the specific nanomaterial used in a particular study, resulting in the use of textual descriptions in research project communications and reporting. To ensure that internal project documentation can later be linked to publicly released data and knowledge for the specific nanomaterials, or even to specific batches and variants of nanomaterials utilised in that project, a new identifier is proposed: the European Registry of Materials Identifier.

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Computational toxicology is central to the current transformation occurring in toxicology and chemical risk assessment. There is a need for more efficient use of existing data to characterize human toxicological response data for environmental chemicals in the US and Europe. The Adverse Outcome Pathway (AOP) framework helps to organize existing mechanistic information and contributes to what is currently being described as New Approach Methodologies (NAMs).

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The adverse outcome pathway (AOP) is a conceptual construct that facilitates organisation and interpretation of mechanistic data representing multiple biological levels and deriving from a range of methodological approaches including , and assays. AOPs are playing an increasingly important role in the chemical safety assessment paradigm and quantification of AOPs is an important step towards a more reliable prediction of chemically induced adverse effects. Modelling methodologies require the identification, extraction and use of reliable data and information to support the inclusion of quantitative considerations in AOP development.

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Article Synopsis
  • Current OECD guidelines for chemical risk assessment rely heavily on animal testing, raising ethical and financial concerns, prompting a push for human-based toxicity testing models.
  • The proposed in vitro multi-organ strategy utilizes human-induced pluripotent stem cells (hiPSCs) to create models of various organs and assesses their sensitivity to the herbicide paraquat (PQ), revealing organ-specific toxic effects and underlying biological pathways impacted by PQ exposure.
  • This innovative approach enhances chemical toxicity evaluation by using human cells to reduce interspecies variation, allowing for more accurate assessments of differential sensitivity across organs and improving overall chemical risk assessments for human health.
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Read-across approaches often remain inconclusive as they do not provide sufficient evidence on a common mode of action across the category members. This read-across case study on thirteen, structurally similar, branched aliphatic carboxylic acids investigates the concept of using human-based new approach methods, such as in vitro and in silico models, to demonstrate biological similarity. Five out of the thirteen analogues have preclinical in vivo studies.

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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).

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The blood-brain barrier (BBB) is a highly restrictive barrier that preserves central nervous system homeostasis and ensures optimal brain functioning. Using BBB cell assays makes it possible to investigate whether a compound is likely to compromise BBBs functionality, thereby probably resulting in neurotoxicity. Recently, several protocols to obtain human brain-like endothelial cells (BLECs) from induced pluripotent stem cells (iPSCs) have been reported.

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Chemoinformatics has developed efficient ways of representing chemical structures for small molecules as simple text strings, simplified molecular-input line-entry system (SMILES) and the IUPAC International Chemical Identifier (InChI), which are machine-readable. In particular, InChIs have been extended to encode formalized representations of mixtures and reactions, and work is ongoing to represent polymers and other macromolecules in this way. The next frontier is encoding the multi-component structures of nanomaterials (NMs) in a machine-readable format to enable linking of datasets for nanoinformatics and regulatory applications.

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The emergence of nanoinformatics as a key component of nanotechnology and nanosafety assessment for the prediction of engineered nanomaterials (NMs) properties, interactions, and hazards, and for grouping and read-across to reduce reliance on animal testing, has put the spotlight firmly on the need for access to high-quality, curated datasets. To date, the focus has been around what constitutes data quality and completeness, on the development of minimum reporting standards, and on the FAIR (findable, accessible, interoperable, and reusable) data principles. However, moving from the theoretical realm to practical implementation requires human intervention, which will be facilitated by the definition of clear roles and responsibilities across the complete data lifecycle and a deeper appreciation of what metadata is, and how to capture and index it.

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Hazard assessment, based on new approach methods (NAM), requires the use of batteries of assays, where individual tests may be contributed by different laboratories. A unified strategy for such collaborative testing is presented. It details all procedures required to allow test information to be usable for integrated hazard assessment, strategic project decisions and/or for regulatory purposes.

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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.

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We aimed to review the interfering effect of DOACs on tests for haemostatic function and then to discuss overcoming these with activated carbon (AC) products, thereby eliminating DOAC issues from test plasmas. Recent relevant articles were reviewed and are discussed. Laboratory tests for DOACs, lupus anticoagulant, factor assays and APC Resistance were carried out in such publications with and without an AC product on various instruments using reagents approved for diagnostic use in well-regulated clinical laboratories.

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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.

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