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Life sciences · Journal article
Frontiers in Toxicology · September 2, 2026
A consensus or society position rather than new primary data.
This is a conceptual and methodological paper proposing a probabilistic next-generation risk assessment (NGRA) framework to replace traditional deterministic chemical risk assessment. The framework integrates quantitative modelling, mechanistic biology, and new approach methodologies to estimate population-level health risks from chemical exposure, with explicit consideration of susceptible and vulnerable groups. No empirical validation, trial data, or clinical outcomes are reported.
Journal article. Exposed populations including pregnant individuals and those with pre-existing diseases; persons exposed to complex chemical mixtures in food, products, and environment.
Probabilistic NGRA framework integrates quantitative modelling, mechanistic biology, and New Approach Methodologies (NAMs) to estimate likelihood of adverse outcomes under realistic exposure scenarios Health Impact Pathways (HIPs) proposed as mechanism to connect molecular perturbations to population-level health indicators, bridging toxicology and epidemiology Framework explicitly distinguishes susceptible groups (e.g. pregnancy) from vulnerable groups (pre-existing disease, higher exposure burdens), addressing gaps in traditional risk assessment
Probabilistic NGRA framework integrates quantitative modelling, mechanistic biology, and New Approach Methodologies (NAMs) to estimate likelihood of adverse outcomes under realistic exposure scenarios
This framework proposes a conceptual shift in how chemical safety is evaluated and communicated to regulators and public health authorities. However, implementation guidance, validation against known health outcomes, or comparative effectiveness data are not presented here.
A methodological framework paper proposing probabilistic next-generation risk assessment for chemical safety evaluation, without empirical trial data or clinical outcomes to support practice change.
This framework proposes a conceptual shift in how chemical safety is evaluated and communicated to regulators and public health authorities. However, implementation guidance, validation against known health outcomes, or comparative effectiveness data are not presented here.
Graded across the dimensions that decide whether you should act, each from what the source actually supports. There is no single score, and where a dimension was not assessed it says so.
What is missing. This record has no reported figures. That is a gap in the analysis, not a judgement about the study.
Human health is continuously challenged by exposure to complex mixtures of chemicals present in food, products, and the environment. Traditional risk assessment (TRA), rooted in mid-20th-century paradigms, relies on deterministic thresholds and animal testing to define safe exposure levels. This approach, while useful for regulatory simplicity, fails to represent real-world variability, mixture effects, and lifelong events, limiting its relevance for public health protection. Here we show that a probabilistic Next-Generation Risk Assessment (NGRA) framework integrating quantitative modelling, mechanistic biology, and New Approach Methodologies (NAMs), can transform toxicological evidence into probability distributions, estimating the likelihood of adverse outcomes under realistic exposure scenarios. Central to this approach are Health Impact Pathways (HIPs), which connect molecular perturbations to population-level health indicators, bridging toxicology and epidemiology. The framework explicitly distinguishes susceptible groups, such as individuals in physiologically sensitive stages like pregnancy, from vulnerable groups, including those with pre-existing diseases or higher exposure burdens, poorly covered in TRA. By covering these groups, probabilistic NGRA enables more inclusive, relevant, and informative evaluations that align with FAIR (Findable, Accessible, Interoperable, Reusable) data principles and minimize animal testing, offering a scientifically grounded framework for improving chemical safety evaluations and public health protection.
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