The long shadow: a toxicological review of chronic exposure, biopersistence, and latent health risks of engineered nanomaterials.
TL;DR
An integrated risk assessment framework is proposed that combines adverse outcome pathway analysis, physiologically-based pharmacokinetic modeling, new approach methodologies, and safe-by-design principles to enable predictive hazard identification and supports evidence-based regulation of existing ENMs while enabling safety evaluation of materials still in development.
Abstract
The proliferation of engineered nanomaterials (ENMs) across industrial and consumer sectors raises unresolved questions about long-term health effects. Current regulatory frameworks, designed for conventional chemicals, inadequately address nanomaterial-specific challenges, particularly biopersistence and tissue accumulation over years. This review examines the mechanistic basis of chronic nanotoxicity by analyzing biokinetic behavior, pathological outcomes, and methodological limitations specific to persistent ENMs. We focus on three pathological endpoints driven by chronic inflammation: pulmonary and hepatic fibrosis from frustrated phagocytosis and inflammasome activation, carcinogenesis promoted by inflammation-driven tumor microenvironments, and neurodegeneration following microglial activation. Our analysis shows that materials combining high aspect ratios, crystalline structure, surface reactivity, and biological persistence present the greatest pathogenic potential, while many ENMs undergo biodegradation or efficient clearance. We identify critical gaps including the impracticality of lifetime bioassays for thousands of material variants, dosimetry challenges in translating experimental doses to realistic exposures, and the absence of validated biomarkers connecting short-term responses to long-term outcomes. We propose an integrated risk assessment framework that combines adverse outcome pathway analysis, physiologically-based pharmacokinetic modeling, new approach methodologies, and safe-by-design principles to enable predictive hazard identification. This framework bridges the gap between mechanistic laboratory findings and regulatory decision-making by stratifying materials according to physicochemical determinants of chronic risk and providing tiered testing strategies proportionate to hazard concern. This approach supports evidence-based regulation of existing ENMs while enabling safety evaluation of materials still in development.