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ONTOX will deliver a generic strategy to create innovative NAMs in order to predict systemic repeated dose toxicity effects that, upon combination with tailored exposure assessment, will enable human risk assessment.

The 6 NAMs will each consist of a computational system based on cutting-edge AI and will be primarily fed by available biological/mechanistic, toxicological/epidemiological, physicochemical, and kinetic data. Data will be consecutively integrated in physiological maps, quantitative adverse outcome pathway networks, and ontology frameworks; data gaps, as identified by AI, will be filled by targeted state-of-the-art in vitro and in silico testing.

PrecisionTox uncovers biomolecular toxicity pathways through simultaneous high-throughput testing across five biomedical model species and human cell lines, using multi-omics and artificial intelligence to identify molecular key events that initiate disease progression. The PrecisionTox approach leverages the shared genetic legacy of toxicity response observed throughout the animal kingdom, providing an alternative to traditional (mammalian) animal testing by deploying an evolutionarily diverse suite of organisms comprising fruit flies, nematodes, water fleas, and embryos of clawed frogs and zebrafish. In addition to this phylogenetic approach, PrecisionTox aims to quantify variation in risk within populations and corresponding exposure thresholds by addressing susceptibility as a heritable trait that varies with genetic diversity.