Altex-Alternatives To Animal Experimentation最新文献

Difficult to test substances, including poorly soluble, mildly irritating, or UVCBs (unknown or variable composition complex reaction products or biological materials), producing weak or borderline in vivo results, face additional challenges in in vitro assays that often necessitate data integration in a weight of evidence (WOE) approach to inform skin sensitization potential. Here we present several case studies on difficult to test substances and highlight the utility of the toxicological priority index (ToxPi) as a data visualization tool to compare skin sensitization biological activity. The case study test substances represent two poorly soluble substances, tetrakis (2-ethylbutyl) orthosilicate and decyl palmitate, and two UVCB substances, alkylated anisole and hydrazinecarboximidamide, 2-[(2-hydroxyphenyl)methylene]-, reaction products with 2 undecanone. Data from key events within the skin sensitization adverse outcome pathway were gathered from publicly available sources or specifically generated. Incorporating the data for these case study test substances as well as data on chemicals of a known sensitization class (sensitizer, irritating non-sensitizer, and non-sensitizer) into ToxPi produced biological activity profiles which were grouped using unsupervised hierarchical clustering. Three of the case study test substances concluded to lack skin sensitization potential by traditional WOE produced biological activity profiles most consistent with non-sensi­tizing substances, whereas the prediction was less definitive for a substance considered positive by traditional WOE. Visualizing the data using bioactivity profiles can provide further support for WOE conclusions in certain circumstances but is unlikely to replace WOE as a stand-alone prediction due to limitations of the method including the impact of missing data points.

While the original definition of replacement focuses on the replacement of the use of animals in science, a more contemporary definition focuses on accelerating the development and use of predictive and robust models, based on the latest science and technologies, to address scientific questions without the use of animals. The transition to animal free innovation is on the political agenda in and outside the European Union. The Beyond Animal Testing Index (BATI) is a benchmarking instrument designed to provide insight into the activities and contributions of research institutes to the transition to animal free innovation. The BATI allows participating organizations to learn from each other and stimulates continuous improvement. The BATI was modelled after the Access to Medicine Index, which benchmarks pharmaceutical companies on their efforts to make medicines widely available in developing countries. A prototype of the BATI was field-tested with three Dutch aca­demic medical centers and two universities in 2020-2021. The field test demonstrated the usability and effectiveness of the BATI as a benchmarking tool. Analyses were performed across five different domains. The participating institutes concluded that the BATI served as an internal as well as an external stimulus to share, learn, and improve institutional strategies towards the transition to animal free innovation. The BATI also identified gaps in the development and implementation of 3R technologies. Hence, the BATI might be a suitable instrument for monitoring the effectiveness of policies. BATI version 1.0 is ready to be used for benchmarking at a larger scale.

In 2019, the US EPA Administrator issued a directive directing the agency away from reliance on vertebrate tests by 2035, whilst maintaining high-quality human health and environmental risk assessments. There is no accepted approach to achieve this. The decade-long duration of the crop protection (CP) chemical R&D process therefore requires both the invention and application of a modernized approach to those CP chemical projects entering corporate research portfolios by the mid-2020s. We conducted problem formulation discussions with regulatory agency scientists which created the problem statement: “Develop, demonstrate, and implement a modern scientifically sound and robust strategy that applies appropriate and flexible exposure and effects characterization without chemical specific vertebrate tests to reliably address risk, uncertainties, and deficiencies in data and its interpretation with equivalent confidence as do the currently accepted test guidelines and meet the regulatory needs of the agencies”. The solution must provide the knowledge needed to confidently conclude human health and environmental protective risk assessments. Exploring this led to a conceptual model involving the creation and parallel submission of a new approach without reliance on chemical-specific vertebrate tests. Assessment in parallel to a traditional package will determine whether it supports some, or all, of the necessary risk management actions. Analysis of any deficiencies will provide valuable feedback to focus development of tools or approaches for subsequent iterations. When found to provide sufficient information, it will form the technical foun­dation of stakeholder engagement to explore acceptance of a new approach to CP chemical risk assessment.

QT prolongation and the potentially fatal arrhythmia Torsades de Pointes are common causes for withdrawing or restricting drugs; however, little is known about similar liabilities of environmental chemicals. Current in vitro-in silico models for testing proarrhythmic liabilities, using human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CM), provide an opportunity to address this data gap. These methods are still low- to medium-throughput and not suitable for testing the tens of thousands of chemicals in commerce. We hypothesized that combining high-throughput population- based in vitro testing in hiPSC-CMs with a fully in silico data analysis workflow can offer sensitive and specific predictions of proarrhythmic potential. We calibrated the model with a published hiPSC-CM dataset of drugs known to be positive or negative for proarrhythmia and tested its performance using internal cross-validation and external validation. Additionally, we used computational down-sampling to examine three study designs for hiPSC-CM data: one replicate of one donor, five replicates of one donor, and one replicate of a population of five donors. We found that the population of five donors had the best performance for predicting proarrhythmic potential. The resulting model was then applied to predict the proarrhythmic potential of environmental chemicals, additionally characterizing risk through margin of exposure (MOE) calculations. Out of over 900 environmental chemicals tested, over 150 were predicted to have proarrhythmic potential, but only seven chemicals had a MOE < 1. We conclude that a high-throughput in vitro-in silico approach using population-based hiPSC-CM testing provides a reasonable strategy to screen environmental chemicals for proarrhythmic potential.

The adverse outcome pathway (AOP) framework plays a crucial role in the paradigm shift of tox­icity testing towards the development and use of new approach methodologies. AOPs developed for chemicals are in theory applicable to nanomaterials (NMs). However, only initial efforts have been made to integrate information on NM-induced toxicity into existing AOPs. In a previous study, we identified AOPs in the AOP-Wiki associated with the molecular initiating events (MIEs) and key events (KEs) reported for NMs in scientific literature. In a next step, we analyzed these AOPs and found that mitochondrial toxicity plays a significant role in several of them at the molecular and cellular levels. In this study, we aimed to generate hypothesis-based AOPs related to NM-induced mitochondrial toxicity. This was achieved by integrating knowledge on NM-induced mitochondrial toxicity into all existing AOPs in the AOP-Wiki, which already includes mitochondrial toxicity as a MIE/KE. Several AOPs in the AOP-Wiki related to the lung, liver, cardiovascular and nervous system, with extensively defined KEs and key event relationships (KERs), could be utilized to develop AOPs that are relevant for NMs. However, the majority of the studies included in our literature review were of poor quality, particularly in reporting NM physicochemical characteristics, and NM-relevant mitochondrial MIEs were rarely reported. This study highlights the potential role of NM-induced mitochondrial toxicity in human-relevant adverse outcomes and identifies useful AOPs in the AOP-Wiki for the development of AOPs for NMs.

Bile acid homeostasis is vital for numerous metabolic and immune functions in humans. The enterohepatic circulation of bile acids is extremely efficient, with ~95% of intestinal bile acids being reabsorbed. Disturbing intestinal bile acid uptake is expected to substantially affect intestinal and systemic bile acid levels. Here, we aimed to predict the effects of apical sodium-dependent bile acid transporter (ASBT)-inhibition on systemic plasma levels. For this, we combined in vitro Caco-2 cell transport assays with physiologically based (PBK) modeling. We used the selective ASBT-inhibitor odevixibat (ODE) as a model compound. Caco-2 cells grown on culture inserts were used to obtain transport kinetic parameters of glycocholic acid (GCA). The apparent Michaelis-Menten constant (Km,app), apparent maximal intestinal transport rate (Vmax,app), and ODE’s inhibitory constant (Ki) were determined for GCA. These kinetic parameters were incorporated into a PBK model and used to predict the ASBT inhibition effects on plasma bile acid levels. GCA is transported over Caco-2 cells in an active and sodium-dependent manner, indicating the presence of functional ASBT. ODE inhibited GCA transport dose-dependently. The PBK model predicted that oral doses of ODE reduced conjugated bile acid levels in plasma. Our simulations match in vivo data and provide a first proof-of-principle for the incorporation of active intestinal bile acid uptake in a bile acid PBK model. This approach could in future be of use to predict the effects of other ASBT-inhibitors on plasma and intestinal bile acid levels.

Adverse outcome pathways (AOPs) provide evidence for demonstrating and assessing causality between measurable toxicological mechanisms and human or environmental adverse effects. AOPs have gained increasing attention over the past decade and are believed to provide the necessary steppingstone for more effective risk assessment of chemicals and materials and moving beyond the need for animal testing. However, as with all types of data and knowledge today, AOPs need to be reusable by machines, i.e., machine-actionable, in order to reach their full impact potential. Machine-actionability is supported by the FAIR principles, which guide findability, accessibility, interoperability, and reusability of data and knowledge. Here, we describe why AOPs need to be FAIR and touch on aspects such as the improved visibility and the increased trust that FAIRification of AOPs provides.

In vitro methods provide a key opportunity to model human-relevant exposure scenarios for hazard identification of inhaled toxicants. Compared to in vivo tests, in vitro methods have the advantage of assessing effects of inhaled toxicants caused by differences in dosimetry, e.g., variations in con­centration (exposure intensity), exposure duration, and exposure frequency, in an easier way. Variations in dosimetry can be used to obtain information on adverse effects in human-relevant exposure scenarios that can be used for risk assessment. Based on the published literature of exposure approaches using air-liquid interface models of the respiratory tract, supplemented with additional experimental data from the EU H2020 project “PATROLS” and research funded by the Dutch Ministry of Agriculture, Nature and Food Quality, the advantages and disadvantages of dif­ferent exposure methods and considerations to design an experimental setup are summarized and discussed. As the cell models used are models for the respiratory epithelium, our focus is on the local effects in the airways. In conclusion, in order to generate data from in vitro methods for risk assessment of inhaled toxicants it is recommended that (1) it is considered what information really is needed for hazard or risk assessment; (2) the exposure system that is most suitable for the chemical to be assessed is chosen; (3) a deposited dose that mimics deposition in the human respiratory tract is used, and (4) the post-exposure sampling methodology should be carefully considered and relevant to the testing strategy used.

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.

Perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA) are the major components of long-chain per- and polyfluorinated alkyl substances (PFAS), known for their chemical stability and environmental persistence. Even if PFOA and PFOS have been phased out or are limited in use, they still represent a concern for human and environmental health. Several studies have been per­formed to highlight the toxicological behavior of these chemicals and their mode of action (MoA). Data have suggested a causal association between PFOA or PFOS exposure and carcinogenicity in humans, but the outcomes of epidemiological studies showed some inconsistency. Moreover, the hypothesized MoA based on animal studies is considered not relevant for human cancer. To improve the knowledge on PFAS toxicology and contribute to the weight of evidence for the regu­latory classification of PFAS, we used the BALB/c 3T3 cell transformation assay (CTA), an in vitro model under consideration to be included in an integrated approach to testing and assessment for non-genotoxic carcinogens (NGTxCs). PFOS and PFOA were tested at several concentrations using a validated experimental protocol. Our results demonstrate that PFOA does not induce cell transformation, whereas PFOS exposure induced a concentration-related increase of type III foci. Malignant foci formation was triggered at PFOS concentrations equal to or higher than 50 ppm and was not directly associated with cytotoxicity or proliferation induction. The divergent CTA outcomes suggest that different molecular events could be responsible for the toxicological profiles of PFOS and PFOA, which were not fully captured in our study.