Both because of the shortcomings of existing risk assessment methodologies, as well as newly available tools to predict hazard and risk with machine learning approaches, there has been an emerging emphasis on probabilistic risk assessment. Increasingly sophisticated AI models can be applied to a plethora of exposure and hazard data to obtain not only predictions for particular endpoints but also to estimate the uncertainty of the risk assessment outcome. This provides the basis for a shift from deterministic to more probabilistic approaches but comes at the cost of an increased complexity of the process as it requires more resources and human expertise. There are still challenges to overcome before a probabilistic paradigm is fully embraced by regulators. Based on an earlier white paper (Maertens et al., 2022), a workshop discussed the prospects, challenges and path forward for implementing such AI-based probabilistic hazard assessment. Moving forward, we will see the transition from categorized into probabilistic and dose-dependent hazard outcomes, the application of internal thresholds of toxicological concern for data-poor substances, the acknowledgement of user-friendly open-source software, a rise in the expertise of toxicologists required to understand and interpret artificial intelligence models, and the honest communication of uncertainty in risk assessment to the public.
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For almost fifteen years, the availability and regulatory acceptance of new approach methodologies (NAMs) to assess the absorption, distribution, metabolism and excretion (ADME/biokinetics) in chemical risk evaluations are a bottleneck. To enhance the field, a team of 24 experts from science, industry, and regulatory bodies, including new generation toxicologists, met at the Lorentz Centre in Leiden, The Netherlands. A range of possibilities for the use of NAMs for biokinetics in risk evaluations were formulated (for example to define species differences and human variation or to perform quantitative in vitro-in vivo extrapolations). To increase the regulatory use and acceptance of NAMs for biokinetics for these ADME considerations within risk evaluations, the development of test guidelines (protocols) and of overarching guidance documents is considered a critical step. To this end, a need for an expert group on biokinetics within the Organisation of Economic Cooperation and Development (OECD) to supervise this process was formulated. The workshop discussions revealed that method development is still required, particularly to adequately capture transporter mediated processes as well as to obtain cell models that reflect the physiology and kinetic characteristics of relevant organs. Developments in the fields of stem cells, organoids and organ-on-a-chip models provide promising tools to meet these research needs in the future.
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Introducing a hyperbolic vortex into a showerhead is a possibility to achieve higher spray velocities for a given discharge without reducing the nozzle diameter. Due to the introduction of air bubbles into the water by the vortex, the spray is pushed from a transition (dripping faucet) regime into a jetting regime, which results in higher droplet and jet velocities using the same nozzle diameter and throughput. The same droplet and jet diameters were realized compared to a showerhead without a vortex. Assuming that the satisfaction of a shower experience is largely dependent on the droplet size and velocity, the implementation of a vortex in the showerhead could provide the same shower experience with 14% less water consumption compared to the normal showerhead. A full optical and physical analysis was presented, and the important chemical parameters were investigated.
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Implementation of reliable methodologies allowing Reduction, Refinement, and Replacement (3Rs) of animal testing is a process that takes several decades and is still not complete. Reliable methods are essential for regulatory hazard assessment of chemicals where differences in test protocol can influence the test outcomes and thus affect the confidence in the predictive value of the organisms used as an alternative for mammals. Although test guidelines are common for mammalian studies, they are scarce for non-vertebrate organisms that would allow for the 3Rs of animal testing. Here, we present a set of 30 reporting criteria as the basis for such a guideline for Developmental and Reproductive Toxicology (DART) testing in the nematode Caenorhabditis elegans. Small organisms like C. elegans are upcoming in new approach methodologies for hazard assessment; thus, reliable and robust test protocols are urgently needed. A literature assessment of the fulfilment of the reporting criteria demonstrates that although studies describe methodological details, essential information such as compound purity and lot/batch number or type of container is often not reported. The formulated set of reporting criteria for C. elegans testing can be used by (i) researchers to describe essential experimental details (ii) data scientists that aggregate information to assess data quality and include data in aggregated databases (iii) regulators to assess study data for inclusion in regulatory hazard assessment of chemicals.
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Schepen in moeilijkheden op zee leveren vaak besluitvormingsproblemen op tussen de scheepseigenaar/kapitein en de kuststaat. Kuststaten en met name de lokale overheden willen een probleem schip graag zo ver mogelijk weg sturen van hun gebied terwijl de eigenaar/kapitein zijn schip graag zo snel mogelijk naar de kust, een beschutte locatie of haven wil brengen. Het onderzoek geeft onderbouwing voor de besluitvorming rond schepen in moeilijkheden, zowel voor de zeescheepvaart als de betrokken besluitvormers van oeverstaten. Het product van het project is: een, op uitgewerkte scenario’s per scheepstype en lading gebaseerde besluitvormingsprocedure voor zeeschepen in moeilijkheden
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Adverse Outcome Pathways (AOPs) are conceptual frameworks that tie an initial perturbation (molecular initiat- ing event) to a phenotypic toxicological manifestation (adverse outcome), through a series of steps (key events). They provide therefore a standardized way to map and organize toxicological mechanistic information. As such, AOPs inform on key events underlying toxicity, thus supporting the development of New Approach Methodologies (NAMs), which aim to reduce the use of animal testing for toxicology purposes. However, the establishment of a novel AOP relies on the gathering of multiple streams of evidence and infor- mation, from available literature to knowledge databases. Often, this information is in the form of free text, also called unstructured text, which is not immediately digestible by a computer. This information is thus both tedious and increasingly time-consuming to process manually with the growing volume of data available. The advance- ment of machine learning provides alternative solutions to this challenge. To extract and organize information from relevant sources, it seems valuable to employ deep learning Natural Language Processing techniques. We review here some of the recent progress in the NLP field, and show how these techniques have already demonstrated value in the biomedical and toxicology areas. We also propose an approach to efficiently and reliably extract and combine relevant toxicological information from text. This data can be used to map underlying mechanisms that lead to toxicological effects and start building quantitative models, in particular AOPs, ultimately allowing animal-free human-based hazard and risk assessment.
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New approach methodologies predicting human cardiotoxicity are of interest to support or even replace in vivo-based drug safety testing. The present study presents an in vitro–in silico approach to predict the effect of inter-individual and inter-ethnic kinetic variations in the cardiotoxicity of R- and S-methadone in the Caucasian and the Chinese population. In vitro cardiotoxicity data, and metabolic data obtained from two approaches, using either individual human liver microsomes or recombinant cytochrome P450 enzymes (rCYPs), were integrated with physiologically based kinetic (PBK) models and Monte Carlo simulations to predict inter-individual and inter-ethnic variations in methadone-induced cardiotoxicity. Chemical specific adjustment factors were defined and used to derive dose–response curves for the sensitive individuals. Our simulations indicated that Chinese are more sensitive towards methadone-induced cardiotoxicity with Margin of Safety values being generally two-fold lower than those for Caucasians for both methadone enantiomers. Individual PBK models using microsomes and PBK models using rCYPs combined with Monte Carlo simulations predicted similar inter-individual and inter-ethnic variations in methadone-induced cardiotoxicity. The present study illustrates how inter-individual and inter-ethnic variations in cardiotoxicity can be predicted by combining in vitro toxicity and metabolic data, PBK modelling and Monte Carlo simulations. The novel methodology can be used to enhance cardiac safety evaluations and risk assessment of chemicals.
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From the article: Abstract Sub-chronic toxicity studies of 163 non-genotoxic chemicals were evaluated in order to predict the tumour outcome of 24-month rat carcinogenicity studies obtained from the EFSA and ToxRef databases. Hundred eleven of the 148 chemicals that did not induce putative preneoplastic lesions in the sub-chronic study also did not induce tumours in the carcinogenicity study (True Negatives). Cellular hypertrophy appeared to be an unreliable predictor of carcinogenicity. The negative predictivity, the measure of the compounds evaluated that did not show any putative preneoplastic lesion in de sub-chronic studies and were negative in the carcinogenicity studies, was 75%, whereas the sensitivity, a measure of the sub-chronic study to predict a positive carcinogenicity outcome was only 5%. The specificity, the accuracy of the sub-chronic study to correctly identify non-carcinogens was 90%. When the chemicals which induced tumours generally considered not relevant for humans (33 out of 37 False Negatives) are classified as True Negatives, the negative predictivity amounts to 97%. Overall, the results of this retrospective study support the concept that chemicals showing no histopathological risk factors for neoplasia in a sub-chronic study in rats may be considered non-carcinogenic and do not require further testing in a carcinogenicity study.
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The first Stakeholder Network Meeting of the EU Horizon 2020-funded ONTOX project was held on 13-14 March 2023, in Brussels, Belgium. The discussion centred around identifying specific challenges, barriers and drivers in relation to the implementation of non-animal new approach methodologies (NAMs) and probabilistic risk assessment (PRA), in order to help address the issues and rank them according to their associated level of difficulty. ONTOX aims to advance the assessment of chemical risk to humans, without the use of animal testing, by developing non-animal NAMs and PRA in line with 21st century toxicity testing principles. Stakeholder groups (regulatory authorities, companies, academia, non-governmental organisations) were identified and invited to participate in a meeting and a survey, by which their current position in relation to the implementation of NAMs and PRA was ascertained, as well as specific challenges and drivers highlighted. The survey analysis revealed areas of agreement and disagreement among stakeholders on topics such as capacity building, sustainability, regulatory acceptance, validation of adverse outcome pathways, acceptance of artificial intelligence (AI) in risk assessment, and guaranteeing consumer safety. The stakeholder network meeting resulted in the identification of barriers, drivers and specific challenges that need to be addressed. Breakout groups discussed topics such as hazard versus risk assessment, future reliance on AI and machine learning, regulatory requirements for industry and sustainability of the ONTOX Hub platform. The outputs from these discussions provided insights for overcoming barriers and leveraging drivers for implementing NAMs and PRA. It was concluded that there is a continued need for stakeholder engagement, including the organisation of a 'hackathon' to tackle challenges, to ensure the successful implementation of NAMs and PRA in chemical risk assessment.
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Development of novel testing strategies to detect adverse human health effects is of interest to replace in vivo-based drug and chemical safety testing. The aim of the present study was to investigate whether physiologically based kinetic (PBK) modeling-facilitated conversion of in vitro toxicity data is an adequate approach to predict in vivo cardiotoxicity in humans. To enable evaluation of predictions made, methadone was selected as the model compound, being a compound for which data on both kinetics and cardiotoxicity in humans are available. A PBK model for methadone in humans was developed and evaluated against available kinetic data presenting an adequate match. Use of the developed PBK model to convert concentration–response curves for the effect of methadone on human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CM) in the so-called multi electrode array (MEA) assay resulted in predictions for in vivo dose–response curves for methadone-induced cardiotoxicity that matched the available in vivo data. The results also revealed differences in protein plasma binding of methadone to be a potential factor underlying variation between individuals with respect to sensitivity towards the cardiotoxic effects of methadone. The present study provides a proof-of-principle of using PBK modeling-based reverse dosimetry of in vitro data for the prediction of cardiotoxicity in humans, providing a novel testing strategy in cardiac safety studies.
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