Chiara Laura Battistelli

The widespread presence of micro- and nanoplastics (MNPs) in the environment represents an emerging risk for human and environment health. New Approach Methodologies (NAMs) offer valuable tools to improve the mechanistic understanding of nanoscale processes and support hazard identification without animal testing. This study investigated the biological effects of exposure to 0–100 µg/mL 100 and 20 nm polystyrene (PS-NPs) and 100 nm polycaprolactone nanoplastics (PCL-NPs) using advanced in vitro intestinal models and the 3R-compliant in vivo Caenorhabditis elegans model. In vitro endpoints included cytotoxicity, oxidative stress, DNA damage, cellular internalization, and barrier integrity, while in vivo analyses focused on oxidative stress and locomotor behavior across multiple exposed generations. PS-NPs induced significant DNA damage in vitro, particularly at ≥50 µg/mL after 24–48 h exposure, and were rapidly internalized by cells, with 20 nm particles also detected in the nucleus. In contrast, 100 nm PCL-NPs elicited weaker biological responses. In vivo, PS-NPs caused an increase in oxidative stress response and locomotor behavior across exposed generations, whereas PCL-NPs produced milder effects, consistent with in vitro findings. These results support the potential of integrated NAMs for assessing human health risks associated with MNP exposure within a One Health framework.

Assessing genotoxicity, specifically gene mutations and chromosomal aberrations, is fundamental to chemical risk assessment. Notably, the early identification of an aneugenic mechanism is of crucial importance, allowing, in principle, for a threshold-based risk assessment approach. To investigate this issue while pushing towards innovation in risk assessment by leveraging New Approach Methodologies, in silico approaches stand out as a particularly promising avenue. Building on these premises and given the lack of QSAR models for aneuploidy in the public domain, the present study exploited the genotoxicity-relevant alert lists implemented in the OECD QSAR Toolbox to base the investigation of structure-activity relationships for aneuploidy. To address the lack of relevant structured data resources, a dataset of 65 confirmed aneugenic substances was specifically curated and designed for the study. The results highlighted widely differing performances among the various profilers, confirming a general limited discriminatory power for aneuploidy. On the other hand, a granular analysis of the results from individual structural alerts enabled the successful isolation of some features associated with the aneugenic mode of action. Moreover, a subset of tubulin-binding chemicals was investigated to determine whether targeting a specific protein improves the characterization of toxicological alerts. The findings provide a refined definition of specific toxicity determinants for tubulin binders and serve as a promising tool for early hazard assessment, potentially informing relevant AOPs. While the computational approach appears promising, the overarching challenge that emerges is the limited availability of well-curated experimental data. In fact, reliable data on aneuploidy are scarce and fragmented across the literature. Furthermore, existing compilations of micronucleus study results are often complicated by conflicting interpretations.

This review comprehensively examines the variability and uncertainty associated with test guideline (TG)-conform genotoxicity data and explores the respective implications for the integration of non-animal-methods (NAMs) into regulatory frameworks. Historical amendments to OECD TGs are mapped to reveal the method’s evolution that improves the scientific quality of the data but also explains data heterogeneity within available databases. An analysis of the major genotoxicity databases ECVAM, ISSMIC, and OASIS demonstrates substantial variability in genotoxicity calls. Using the EFSA genotoxicity database, which currently harbours the best-curated (meta-) data, we estimate that 22–77% of compounds exhibit similarity of replicate results below 85%, depending on the assay. The potentially most important variables statistically explaining variability and sensitivity were analysed. The practical limitations to identify them with high reliability and to define their optimum needs to be accepted as a qualitative baseline uncertainty. These findings underscore the necessity of contextualizing NAM performance evaluations within the intrinsic variability and uncertainty of animal and in vitro reference data. We propose that this variability is explicitly considered in the development and validation of NAM-based Integrated Approaches for Testing and Assessment. This review provides a critical foundation for regulators and scientists aiming to enhance the acceptance and utility of NAMs in genotoxicity assessment.

This review comprehensively examines the variability and uncertainty associated with test guideline (TG)-conform genotoxicity data and explores the respective implications for the integration of non-animal-methods (NAMs) into regulatory frameworks. Historical amendments to OECD TGs are mapped to reveal the method’s evolution that improves the scientific quality of the data but also explains data heterogeneity within available databases. An analysis of the major genotoxicity databases ECVAM, ISSMIC, and OASIS demonstrates substantial variability in genotoxicity calls. Using the EFSA genotoxicity database, which currently harbours the best-curated (meta-) data, we estimate that 22–77% of compounds exhibit similarity of replicate results below 85%, depending on the assay. The potentially most important variables statistically explaining variability and sensitivity were analysed. The practical limitations to identify them with high reliability and to define their optimum needs to be accepted as a qualitative baseline uncertainty. These findings underscore the necessity of contextualizing NAM performance evaluations within the intrinsic variability and uncertainty of animal and in vitro reference data. We propose that this variability is explicitly considered in the development and validation of NAM-based Integrated Approaches for Testing and Assessment (IATAs). This review provides a critical foundation for regulators and scientists aiming to enhance the acceptance and utility of NAMs in genotoxicity assessment.

The Caco-2 in vitro model of the intestinal barrier is a well-established system for the investigation of the intestinal fate of orally ingested chemicals and drugs, and it has been used for over ten years by pharmaceutical industries as a model for absorption in preclinical studies. The Caco-2 model shows a fair correlation with in vivo drug absorption, though some inherent biases remain unresolved. Its main limitation lies in the lack of structural complexity, as it does not replicate the diverse cell types and mucus layer present in the human intestinal epithelium. Consequently, the development of advanced in vitro models of the intestinal barrier, that more structurally resemble the human intestinal epithelium physiology, has increased the potential applications of these models. Recently, Caco-2-based advanced intestinal models have proven effective in predicting nanomaterial uptake and transport across the intestinal barrier. The aim of this review is to provide a state-of-the-art of human in vitro intestinal barrier models for the study of translocation/uptake of nanoparticles relevant for oral exposure, including inorganic nanomaterials, micro/nano plastic, and fiber nanomaterials. The main effects of the above-mentioned nanomaterials on the intestinal barrier are also reported.

Data generated using new approach methodologies (NAMs), including in silico, in vitro, and in chemico approaches, are increasingly important for the hazard identification of chemicals. Among NAMs, (quantitative) structure–activity relationship (Q)SAR models occupy a peculiar position by allowing (in principle) a toxicity estimate on the sole basis of chemical structural information, leveraging upon toxicity profiles of already tested chemicals (a training set). Consequently, the metrics adopted for the estimation of both the congruence of the test chemicals with the training set and the risk categorization are of paramount importance. This paper comprises a small-scale, mainly methodological study to investigate these aspects and assess the general coherence between the results from different (Q)SAR models applied to the assessment of the carcinogenicity of pesticide-active substances and metabolites. The results of the present study underline the significant potential of using (Q)SAR models, together with limitations, such as inconsistencies in results across models and the intrinsic constraints of their applicability domain. The critical role of a priori strategies adopted in defining the applicability domain of the models is highlighted, emphasizing the need for user-transparent definitions. This is a crucial step for a sensible integration of the information coming from different NAMs.

Safe and sustainable chemicals/materials are critical for achieving European green goals. The novel SSbD framework aims to harmonize assessments during innovation. Here, we discuss the essential role of FAIR data and tools in operationalizing SSbD.