Altex-Alternatives To Animal Experimentation最新文献

The Virtual Human Platform for Safety Assessment (VHP4Safety) project aims to build a virtual human platform (VHP) to protect human health and revolutionize the safety assessment of chemicals and pharmaceuticals by transitioning from animal-based to human-based approaches. The goal of this article is to introduce the project and its interdisciplinary approach to co-creation with mul­tiple academic, regulatory, industrial and societal partners covering the entire safety assessment knowledge chain. Three research lines drive the project: 1) building the VHP; 2) feeding the VHP with human data; and 3) implementing the VHP. The project focusses on three case studies that incor­porate human-relevant scenarios not included in current animal-based safety assessment strategies. The VHP is built on tools and services, including pharmacokinetic and computational models, and integrates several data sources within each case study, including data on human physiology, epi­demiology, toxicokinetic and -dynamic parameters, as well as data on chemical characteristics and exposures. In addition, the VHP integrates new data generated within the project using new approach methodologies representing key events within adverse outcome pathways. Implemen­tation of the VHP is investigated using an innovation systems approach, engaging stakeholders, and organizing training and education. Central to the VHP4Safety project is our co-creative approach, which is facilitated by biannual designathons and hackathons that foster active involvement of all project participants from over 30 partner organizations. By integrating technological innovations with transparency and stakeholder collaboration, the VHP4Safety project will help shape the tran­sition to next generation safety assessment in which animal testing becomes redundant.

Performance of pharmacokinetic models developed using in-vitro-to-in-vivo extrapolation (IVIVE) methods may be improved by refining assumptions regarding fraction absorbed (Fabs) through the intestine, a component of oral bioavailability (Fbio). Although in vivo measures of Fabs are often unavailable for non-pharmaceuticals, in vitro measures of apparent permeability (Papp) using the Caco-2 cell line have been highly correlated with Fabs. We measured bidirectional Papp for over 400 non-pharmaceutical chemicals using the Caco-2 assay. A random forest quantitative structure-property relationship (QSPR) model was developed using these and peer-reviewed pharmaceutical data. Both Caco-2 data (R2 = 0.37) and the QSPR model (R2 = 0.29) were better at predicting human bioavailability compared to in vivo rat data (R2 = 0.23). After incorporation into a high-throughput toxicokinetics (HTTK) framework for IVIVE, the Caco-2 data were used to estimate in vivo administered equivalent dose (AED) for bioactivity assessed in vitro. The HTTK-predicted plasma steady state concentrations (Css) for IVIVE were revised, with modest changes predicted for poorly absorbed chemicals. Experimental data were evaluated for sources of measurement uncertainty, which were then accounted for using the Monte Carlo method. Revised AEDs were subsequently compared with exposure estimates to evaluate effects on bioactivity:exposure ratios, a surrogate for risk. Only minor changes in the margin between chemical exposure and predicted bioactive doses were observed due to the preponderance of highly absorbed chemicals.

An essential aspect of the EU’s Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH) regulation is the European Chemicals Agency’s (ECHA) evaluation of testing proposals submitted by registrants to address data gaps. Registrants may propose adaptations, such as read-across, to waive standard testing; however, it is widely believed that ECHA often finds justifications for read-across hypotheses inadequate. From 2008 to August 2023, 2,630 testing proposals were submitted to ECHA; of these, 1,538 had published decisions that were systematically evaluated in this study. Each document was manually reviewed and information extracted for further analyses, focusing on 17 assessment elements (AEs) from the Read-Across Assessment Framework (RAAF) and testing proposal evaluations (TPE). Each submission was classified as to the AEs relied upon by the registrants and by ECHA. Data was analyzed for patterns and associations. Adaptations were included in 23% (350) of proposals, with analogue (168) and group (136) read-across being most common. Of the 304 read-across hypotheses, 49% were accepted, with group read-across showing significantly higher odds of acceptance. Data analysis examined factors such as tonnage band (Annex), test guidelines, hypothesis AEs, and structural similarities of target and source sub­stances. While decisions were often context-specific, several significant associations influencing acceptance emerged. Overall, this analysis provides a comprehensive overview of 15 years of experience with testing proposal-specific read-across adaptations by both registrants and ECHA. These data will inform future submissions as they identify most critical AEs to increase the odds of read-across acceptance.

Systematic reviews (SRs) contribute to implementing the 3Rs in preclinical research. With the ever-increasing amount of scientific literature, SRs require increasing time investment. Thus, using the most efficient review tools is essential. Most available software tools aid the screening process; tools for data extraction and/or multiple review phases are relatively scarce. Using a single platform for all review phases allows auto-transfer of references from one phase to the next and enables work on multiple phases at the same time. We performed succinct formal tests of four multiphase review tools that are free or relatively affordable: Covidence, Eppi, SRDR+ and SYRF. Our tests comprised full-text screening, sham data extraction, and discrepancy resolution in the context of parts of a systematic review. Screening was performed as per protocol. Sham data extraction comprised free text, numerical and categorial data. Both reviewers logged their experiences with the platforms throughout. These logs were qualitatively summarized and supplemented with further user experi­ences. We show value of all tested tools in the SR process. Which tool is optimal depends on multiple factors, comprising previous experience with the tool but also review type, review questions, and review team member enthusiasm.

Toxicological test methods generate raw data and provide instructions on how to use these to determine a final outcome such as a classification of test compounds as hits or non-hits. The data processing pipeline provided in the test method description is often highly complex. Usually, multiple layers of data, ranging from a machine-generated output to the final hit definition, are considered. Transition between each of these layers often requires several data processing steps. As changes in any of these processing steps can impact the final output of new approach methods (NAMs), the processing pipeline is an essential part of a NAM description and should be included in reporting templates such as the ToxTemp. The same raw data, processed in different ways, may result in different final outcomes that may affect the readiness status and regulatory acceptance of the NAM, as an altered output can affect robustness, performance, and relevance. Data management, pro­cessing, and interpretation are therefore important elements of a comprehensive NAM definition. We aim to give an overview of the most important data levels to be considered during the devel­opment and application of a NAM. In addition, we illustrate data processing and evaluation steps between these data levels. As NAMs are increasingly standard components of the spectrum of toxi­cological test methods used for risk assessment, awareness of the significance of data processing steps in NAMs is crucial for building trust, ensuring acceptance, and fostering the reproducibility of NAM outcomes.

AcutoX is a human in vitro test method for the evaluation of acute oral toxicity developed using a library of 67 curated test chemicals. These chemicals cover a wide variety of chemistries, indus­trial sectors, rodent toxicities, and all EPA and GHS hazard categories. The test uses two different cytotoxicity endpoints (neutral red uptake and MTT metabolism), performed both in the presence and absence of pooled human liver extract (S9), to produce four EC50 values. The EC50 values are used in prediction models to assign a “highly toxic” and “low toxicity” category for both EPA and GHS classification, which can be further refined to assign a hazard category. The binary “highly toxic” / “low toxicity” prediction model has an accuracy of 73.8% and 63.1% for EPA and GHS, respectively, with the subsequent hazard categorization offering a protective prediction (correct or higher category) in 90.0% and 93.3% of cases, respectively. Moreover, the AcutoX test can identify chemicals activated or detoxified by liver metabolism.

Currently, the OECD has adopted three defined approaches (DAs) for eye hazard identification of non-surfactant liquids and solids (TG 467) according to the three UN GHS categories. We are now expanding the applicability domain with a new DA for chemicals having surfactant properties (DASF). It is based on a combination of recombinant human cornea-like epithelium test methods (TG 492: EpiOcular™ EIT or SkinEthic™ HCE EIT) and a modification of the Short Time Exposure (TG 491) method. The aim of the current study was to compare the performance of the DASF with the performance of other NAMs currently included in the OECD TGs and with the classification based on the Draize eye test to identify potential additional DAs. The minimum performance criteria (75% Cat. 1, 50% Cat. 2, 70% No Cat.) used for the adoption of the DAs currently included in TG 467 were used for this purpose. The DASF identified 90.9% of Cat. 1 (N = 23), 77.8% of Cat. 2 (N = 9), and 76.0% of No Cat. (N = 17) surfactants, meeting the minimum performance criteria. Some of the NAMs that are currently included in the TGs seem promising methods to become part of a DA to identify Cat. 1 or No Cat. for eye hazard assessment of surfactants. However, the number of surfactants that have been tested to evaluate their reliability and relevance was often too low. To date, the DASF is the only DA that has evaluated a sufficiently large number of surfactants and whose performance meets the minimum performance criteria.

Hormone signaling plays an essential role during fetal life and is vital for brain development. Endo­crine-disrupting chemicals can interfere with the hormonal milieu during this critical time-period, disrupting key neurodevelopmental processes. Hence, there is a need for the development of assays that evaluate developmental neurotoxicity (DNT) induced by an endocrine mode of action. Herein, we evaluated the neural progenitor C17.2 cell line as an in vitro test system to aid in the detection of endocrine disruption-induced DNT. For this, C17.2 cells were exposed during 10 days of dif­ferentiation to agonists and antagonists of the thyroid hormone (THR), glucocorticoid (GR), retinoic acid (RAR), retinoic x (RXR), oxysterol (LXR), estrogen (ER), androgen (AR), and peroxisome prolif­erator activated delta (PPARβ/δ) receptors, as well as to the agonist of the vitamin D (VDR) receptor. Upon exposure and differentiation, neuronal morphology (neurite outgrowth and branching) and the percentage of neurons in culture were assessed by immunofluorescence. For this, the cells were stained for βIII-tubulin (neuronal marker). C17.2 cells decreased neurite outgrowth and branching in response to RAR, RXR and PPARβ/δ agonists. Exposure to the GR agonist increased the number of cells differentiating into neurons, while exposure to the RXR agonist had the opposite effect. With this approach, we demonstrate that C17.2 cells are responsive to GR, RAR, RXR, and PPARβ/δ agonists and hence could be useful to develop a test system for hazard assessment of endocrine disruption-induced DNT.