ONTOX Insights #8

Next generation risk assessment (NGRA) relies on animal-free New Approach Methodologies (NAMs) to generate data on chemical hazards, toxicokinetics (ADME), and exposure. Although the required data types are widely agreed upon, processes for collecting, integrating, and reporting this information remain insufficiently standardized.
To address this gap, the Alternative Safety Profiling Algorithm (ASPA) was developed, providing a transparent and reproducible workflow that documents and integrates all relevant information. ASPA ensures full traceability of safety assessments, clearly outlining the steps and justifications that lead to final decisions, with the objective that identical data inputs yield identical outcomes across independent assessors.
To facilitate implementation, the ASPA-assist software guides users through the workflow and generates a comprehensive, standardized report capturing all data, methods, intermediate decisions, and uncertainties. Case studies demonstrate ASPA’s applicability across different regulatory contexts, supporting more consistent and reliable NGRA-based safety assessments.

Drug-induced liver injury (DILI) is a rare but serious adverse reaction with diverse clinical presentations. While hepatocellular, cholestatic, and mixed phenotypes are well characterized, steatosis-associated DILI (DIS) remains underexplored despite evidence suggesting that steatosis is common among DILI patients. In this study, a comprehensive search across seven databases identified relevant studies, which were screened using the AI-based platform Sysrev. Clinical, biochemical, and histopathological data were extracted, and drug properties were compiled from public databases or generated via QSAR modelling. The resulting dataset was analysed using statistical and multivariate approaches, including logistic regression.
In total, 251 DIS cases linked to 34 drugs were evaluated. Patients clustered into three subphenotypes associated with recovery, chronicity, or fatal outcomes. Chronic cases were characterized by fibrosis and macrosteatosis, and fatal cases frequently involved microsteatosis and lactic acidosis. Fatal outcomes were mostly associated with drugs such as didanosine, zidovudine, valproate, and tetracycline. A predictive model integrating clinical and chemical features enabled the identification of high-concern drugs and hazardous structural attributes.

Ensuring chemical safety is essential for protecting human health, yet current assessment approaches face major limitations as they are struggling to keep pace with the rapidly increasing number of substances requiring evaluation while continuously relying on animal testing, that society expects to be phased out. To address this challenge, the European Partnership for Alternative Approaches to Animal Testing (EPAA) proposed a novel framework for classifying systemic toxicity using NAMs.
A key component of this framework is the categorization of substances into classes of Potential Systemic Availability (PSA) concern—low, medium, or high. However, practical implementation of this concept has remained unclear. In this study, the authors define health-protective PSA concern classes and introduce a quantitative method for their assessment using high-throughput physiologically based kinetic modelling. Applying this approach, 139 of 150 compounds from the EPAA NAM Designathon were successfully classified.
This shows that while toxicokinetic properties can guide chemical prioritisation, PSA alone is insufficient. Integrating bioactivity data will be essential to fully realize the potential of this framework and strengthen next-generation, NAM-based chemical risk assessment.

New Approach Methodologies (NAMs) are transforming toxicology by providing reliable, human-relevant alternatives to traditional animal testing. This review presents a structured six-step framework that guides NAMs from early development to regulatory approval, illustrated through the example of the Developmental Neurotoxicity (DNT) in vitro battery (IVB).
The lifecycle begins with the development of robust, human-relevant test systems, followed by the creation of a NAM-based roadmap aligned with regulatory needs and early stakeholder engagement. Method readiness is then evaluated for biological relevance, reproducibility, and reliability. Technical characterization, independent expert review, and transparent data sharing are included in scientific validation procedure. OECD recognition ensures rigorous assessment before inclusion in official guidelines, while providing public availability through Contract Research Organizations (CROs) under Good Laboratory Practice (GLP) supports regulatory implementation.
This demonstrates how NAMs can be systematically advanced and continuously refined with scientific progress.

The Adverse Outcome Pathway (AOP) concept supports rapid hazard assessment for human health risks and is continuously expanded within the OECD-supported AOP-Wiki database. This study explores the biological areas and gaps within the AOP-Wiki providing a summary and structured mapping of the diseases and biological processes by already developed AOPs.
Using a multi-step bioinformatics approach, data from the AOP-Wiki were analyzed through overrepresentation analyses (Gene Ontology and DisGeNET). This enabled classification of AOPs and the development of AOP networks, offering a broader system-level overview.
The analysis showed that AOPs most frequently address diseases of the genitourinary system, neoplasms, and developmental anomalies. Three priority areas of the EU PARC project—immunotoxicity and non-genotoxic carcinogenesis, endocrine and metabolic disruption, and developmental and adult neurotoxicity—were further evaluated to identify under- and over-represented outcomes and research gaps.
Overall, the findings enhance understanding of how molecular events relate to adverse health outcomes and support more refined risk assessment approaches. The study also highlights the importance of ensuring that AOP data follow FAIR principles to maximize their scientific and regulatory value.

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