NAM journal最新文献

Cytotoxicity and proliferation measurements are widely used in OECD in vitro test guidelines but do not represent a uniform endpoint. Their regulatory meaning depends on assay role, where they may function as classification endpoints, predictive surrogates, validity criteria, or constraints for concentration selection. These roles differ in biological interpretation, timing, and decision consequences. This review analyzes the context-dependent use of cytotoxicity, cytostasis, and proliferation metrics across OECD methods and emphasizes how endpoint biology, timing, and assay role determine the interpretation of reported viability-type values. Fixed cytotoxicity thresholds are applied as operational decision criteria but often overlap with assay variability, requiring uncertainty-aware interpretation. Excessive cytotoxicity may further compromise interpretability through non-specific stress and assay interference. Cytotoxicity should therefore be treated as a role-specific method-performance parameter requiring explicit definition of endpoint biology, timing, variability, and decision criteria. Good In Vitro Method Practices (GIVIMP)-aligned implementation would improve transparency, reproducibility, and regulatory interpretability of cytotoxicity-based decisions.

The H295R assay (OECD TG456) is used to screen chemicals for interference with steroidogenesis, measuring testosterone and estradiol levels as endpoints. Focusing on these two hormones, however, may overlook informative changes in other steroid classes, particularly progestogens and glucocorticoids. Here, we extended the effect-based H295R-CALUX® read-out to include progestogens and glucocorticoids using PR- and GR CALUX® assays. First, we evaluated whether PR- and GR-CALUX® could be used as H295R read-outs by determining whether control samples produced adequate hormone levels and whether responses to control compounds forskolin and prochloraz met predefined criteria. Progestogenic and glucocorticoid activity was consistently quantifiable, forskolin induced both modalities above the predefined threshold, and prochloraz inhibited glucocorticoid activity while increasing progestogenic activity, consistent with upstream pathway inhibition. The extended H295R-CALUX® read-out was then applied to analyse a set of conazoles. Each conazole was first pre-screened for ERα/AR/PR/GR agonism or antagonism and for cytotoxicity to avoid interference from direct receptor activation and cytotoxicity in the H295R read-out. In the H295R assay, all conazoles except 1,2,4-triazole, affected at least one hormone modality, with a common pattern of reduced androgenic, estrogenic and glucocorticoid activity and compound-specific increases or decreases in progestogenic activity. Further, targeted LC-MS/MS steroid profiling mirrored the effect-based results obtained with the H295R-CALUX® read-out and supported the hypothesis of CYP17A1-related perturbations for some conazoles. Overall, the addition of progestogen and glucocorticoid read-outs, alongside androgen and estrogens, enhances the resolution of the H295R assay, hence improving its relevance for endocrine safety assessment.

Chemical risk assessment is moving away from traditional animal-based testing toward New Approach Methodologies (NAMs) that are more human-relevant, efficient, and aligned with the replacement, reduction, and refinement of animal use. This transition depends not only on new methods and technologies, but also on the researchers who will develop, apply, and promote them. Early-career researchers (ECRs) are central to this effort, yet they often work within fragmented professional networks and have limited opportunities for mentoring, visibility, and leadership. The ASPIS Academy (AA) was established within the ASPIS cluster, comprising the EU Horizon 2020-funded projects ONTOX, RISK-HUNT3R, and PrecisionTox, to support ECRs working on NAM-based chemical risk assessment. Built and coordinated by ECRs with support from senior advisors, AA evolved from an initial idea into an operational network offering training, mentoring, mirroring, twinning, communication, dissemination, and collaboration activities. Its development was shaped not only by strategic planning, but also by the practical realities of voluntary coordination and the changing needs of ECRs across large multidisciplinary consortia. This manuscript presents the establishment, growth, and legacy planning of AA as a case study for building ECR networks in collaborative research environments. We describe the decisions, challenges, lessons learned, and activities that helped the network become useful to its community and provide a practical blueprint for other consortia seeking to support the next generation of NAM scientists. The AA experience demonstrates that empowering ECRs to lead can strengthen scientific communities and accelerate the uptake of NAMs.

Metabolic dysfunction associated steatotic liver disease (MASLD) is one of the most predominant liver disorders. MASLD is associated with dietary intake of fatty acids. Among them, oleic (OA) and palmitic (PA) acids are the most abundant. Furthermore, OA was reported to have an hepatoprotective effect against PA toxicity on primary hepatocytes and liver cell lines. In this work, to characterize the mechanisms related to fatty acids exposure, we analyzed the metabolomic signatures of HepG2/C3A using advanced organ-on-chip technology. The cells were exposed for 2 to 7 days to OA, PA and OA/PA mixture. The cell secretions were analyzed using GC-MS spectrometry to reveal their metabolomic signatures. We were able to identify a common HepG2/C3A response to OA, PA and OA/PA deciphering the FFAs global perturbations including the nitrogen metabolism, after 7 days of treatments. Then, we extracted the specificity of each treatment. We found that OA altered intracellular lipid secretion, while OA/PA shifted metabolism from the lipid production to their consumption. PA exposure induced changes consistent with a perturbation in oxidative stress, energy metabolism and a high oxalic acid production. Nicotinamide levels increased in all treatments, indicating a potential in vitro exposure biomarker of FFA, and a potential mechanistic candidate for further validation in preclinical and clinical settings as its protective effect against liver steatosis was reported in literature. These findings highlight the intricate metabolic responses to FFAs exposure in hepatocytes, suggesting potential biomarkers and pathways for liver-related disorders.

In vitro studies are widely used to measure chemical neurotoxicity or neuroactivity. To show similar activity in vivo, chemicals need to cross the blood-brain barrier (BBB), a membrane that controls chemical movement from the bloodstream to the brain. Machine learning (ML) models present a rapid, cost-effective alternative to experimental methods for predicting BBB permeability. We developed and validated a set of ML models to predict BBB permeability by employing various molecular descriptors and ML algorithms. Models were rigorously evaluated using 5-fold cross-validation and scaffold splitting approaches. Balancing techniques were utilized to address dataset imbalance. Predictions from individual models were combined into a consensus model, which demonstrated the most robust and stable performance. After applying data-balancing techniques, the final consensus model achieved a balanced accuracy of 0.81 for the scaffold splitting validation. SHAP (SHapley Additive exPlanations) analysis identified the topological polar surface area (TopoPSA) as the most critical molecular feature affecting BBB permeability. Additionally, we identified 88 molecular fragments frequently found in BBB-permeable compounds, with nitrogen-containing rings being the most common. Regression model development was more challenging; the Graph Neural Network model performed best with a coefficient of determination (R²) of 0.48. The practical utility of the consensus model was demonstrated by screening 6031 compounds identified by in vitro assay as dopamine D2 receptor (DRD2) antagonists. The consensus model predicted that 27% of these compounds would not cross the BBB in vivo, highlighting how this model can be used to deprioritize in vitro assay testing of chemicals that will likely produce false positive results.

The term "New Approach Methodologies" (NAMs) comprises a plethora of approaches with the potential for testing the safety, efficacy, and biological effects of chemicals, pharmaceuticals, and other substances without relying exclusively on traditional animal testing methodologies. While it is debateable whether "new" is the appropriate terminology - some NAMs have been around for several decades, while others have been developed recently - many scholars have observed that the effective uptake of NAMs in regulatory toxicology remains a challenge. The interdisciplinary CHANGE project applies a systems thinking approach to this challenge by modelling the behaviour of the regulatory toxicology system shaped by system-level factors and their interconnections. This article reports findings from two three-day workshops held in Oslo in summer 2024 (Workshop 1 "Explore") and 2025 (Workshop 2 "Reflect") with experienced practitioners from regulatory agencies, industry, civil society organisations and academia. Through structured collaborative activities, including small- and large-group discussions, modelling exercises and reflection activities, considerable qualitative data was gathered. Most sessions were recorded, transcribed, and analysed using a multi-step thematic analysis explicitly guided by systems thinking principles, enabling the identification of systemic structures and feedback mechanisms and their visualization in the form of a systems model. Insights from Workshop 1 "Explore" were revisited and stress-tested in Workshop 2 "Reflect", deepening the robustness of the resulting systems model. This systems model shows structural, economic, social, cultural and technical factors that are interlinked through reinforcing and balancing feedback loops that promote or inhibit the effective use of NAMs. The systems model shows potential leverage points for system change, for instance enhancing the stability and reliability of the supply chain or ensuring that actors in the regulatory toxicology system have both educational and institutional support to effectively change established practices.

Background: Preclinical assessment of drug safety, efficacy and pharmacokinetics still relies largely on animal‑derived data, despite their limited ability to predict human outcomes. New Approach Methodologies (NAMs) are emerging as more human‑relevant preclinical tools. This systematic evidence synthesis examines (1) current levels and temporal trends in clinical drug attrition and (2) the proportion of failures attributed to biological factors such as safety, efficacy and pharmacokinetics that are routinely evaluated during preclinical testing, to identify priority areas for NAM implementation.

Methods and findings: We systematically searched PubMed on March 5, 2024, for peer-reviewed, English-language studies since 1963 reporting numerical primary data on clinical drug attrition rates and/or reasons for failure. The protocol was prospectively registered (osf.io/46mw5). We excluded non-original research and studies on specific cases, diseases, or single drug classes. Thirty-two publications met the criteria, yielding 60 attrition and 36 failure-reason datasets (1963-2017). Across six decades, mean clinical attrition ranged from ∼80 to ∼91 % with the highest rates within the past two decades. Overall, biological factors (safety, efficacy, pharmacokinetics) accounted for ∼77% of reported causes. Limitations include heterogeneous reporting, restriction to English, and exclusion of grey literature.

Conclusions: Clinical drug attrition has not improved in the last six decades, peaking at ∼91% in the 2000s-2010s, with most failures linked to biological factors. These findings suggest that prevailing preclinical approaches - many of which heavily rely on animal models - often have limited ability to predict clinical outcomes and highlight the urgent need for more predictive, human-relevant NAMs.

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Most in vitro chemical safety workflows are performed in ambient air, although many human tissues experience substantially lower physiological oxygen levels. This mismatch can alter redox tone, stress-response signaling, and interpretation of chemical effects. Here, we present R3ACT (Redox & Antioxidant Capacity Tracker), an animal-free, oxygen-controlled live-cell NAM for mechanistic profiling of redox perturbation and antioxidant-response activation. In human HaCaT keratinocytes adapted to 5 kPa O₂, R3ACT combines viability-gated concentration selection, oxygen-controlled plate-reader measurements, high-content microscopy, and deep-learning-assisted single-cell analysis. The workflow integrates cytosolic and mitochondrial HyPer7.2 biosensors for H₂O₂ dynamics with POINTER, an Nrf2 transcriptional reporter, to assess antioxidant-response engagement. As proof of concept, four exposure-relevant materials were profiled in the main screen, with iron formulations assessed as additional pharmaceutical case examples. Zinc oxide produced the strongest reproducible Nrf2 activation across two independent runs, confirmed by single-cell microscopy. Polystyrene nanoplastics likewise showed reproducible, microscopy-confirmed Nrf2 activation, whereas perfluorooctanoic acid showed a borderline response that was not confirmed by microscopy. Salicylic acid induced Nrf2 activation under physiological oxygen and was interpreted as antioxidant-response engagement rather than skin-sensitization classification. HyPer7.2 provided compartment-specific mechanistic context, but often revealed transient fluctuations rather than consistent material-induced H₂O₂ increases. Together, these data position R3ACT as an early-stage, oxygen-controlled NAM that may support animal-free chemical and drug-screening workflows by generating mechanistic redox/Nrf2 response profiles for compound prioritization. Further benchmarking, predefined performance criteria, and inter-laboratory studies are required before regulatory applicability can be assessed.

Three-dimensional (3D) cell-culture and organ-mimetic systems are transforming biomedical research by offering physiologically relevant models for drug screening, toxicology and regenerative medicine. With enactment of the U.S. FDA Modernization Act 2.0 (2022) and the introduction of Act 3.0 (2024), the European Medicines Agency (EMA)'s endorsement of new approach methodologies (NAMs) and UK government's roadmap to replace animal testing (2025) the regulatory science has shifted toward human-relevant models. However, the development of these technologies in India remains limited to a few leading institutes. This manuscript presents a perspective on adoption of a national strategy for popularizing 3D culture and regenerative biomedical solutions within Indian institutions, with the long-term goal of integrating them into the central drugs standard control organisation (CDSCO), biotechnology for economy, environment, and employment (BioE3) and anusandhan national research foundation (ANRF) mandates, thus aligning them with the India Vision 2047. It reviews Indian and global landscape, identifies skill and infrastructure gaps, and proposes policy and implementation frameworks, emphasizing on capacity building, regulatory incentives and industry-academia collaboration. A roadmap for establishing regional hubs and harmonized standards has been proposed to enable India to emerge as a Global South leader in ethical and cost-effective alternatives-to-animal testing.