Particle-adapted next-generation risk assessment of micro- and nanoplastics from food contact materials: Integrating...

Micro- and nanoplastics (MNPs) released from food contact materials (FCMs) present a risk-assessment challenge because exposure depends not only on mass concentration but also on particle size, number, morphology, polymer identity, surface properties, aggregation, transformation, and co-migration of additives and non-intentionally added substances. Conventional approaches remain fragmented and are poorly suited to translating FCM-specific particle release into human-relevant internal dosimetry and mechanistic toxicity. This review proposes a particle-adapted next-generation risk assessment (NGRA) framework integrating FCM release characterization, gastrointestinal transformation and absorbed fraction, physiologically based toxicokinetic (PBK/PBTK) modelling, adverse outcome pathways (AOPs), and explainable artificial intelligence (XAI). The framework explicitly defines data hand-offs between modules, including particle-specific exposure metrics, internal particle burden, persistence and clearance parameters, key-event evidence, and model uncertainty. AOPs are used to organize mechanistic evidence rather than infer causality, while XAI is positioned as an interpretability and prioritization tool subject to applicability-domain assessment, external validation, reproducibility, and uncertainty analysis. Attention is given to distinguishing particle-mediated effects from those associated with co-migrating additives and non-intentionally added substances. Regulatory translation is considered in the context of FCM migration assessment and emerging NAM-based approaches. The framework provides a basis for evidence integration, testing prioritization, and future quantitative regulatory assessment of FCM-derived MNPs.