Parameterisation of PBK models to predict early-life chemical exposure across biological barriers: Applications to placental, blood-brain barrier, and lactational transfer

Physiologically-based kinetic (PBK) models enable mechanistic prediction of internal chemical exposure across biological systems and support quantitative in vitro-to-in vivo extrapolation (QIVIVE) of in vitro bioactivity or toxicity data within next-generation risk assessment (NGRA). A major challenge, however, is the parameterisation of chemical transfer across specialised biological barriers (particularly the placenta, blood-brain barrier (BBB), and mammary epithelium), which govern exposure of the foetus, (developing) brain, and breastfed infant. These barriers undergo pronounced structural and functional maturation, and their permeability, transporter activity, and physiological characteristics vary with gestational age and lactation stage, complicating quantitative prediction of target-site dosimetry. This review presents a structured, FAIR (Findable, Accessible, Interoperable, and Reusable)-aligned framework for parameterising PBK models describing chemical transfer across these three developmental barriers. Within NGRA, human in vivo toxicokinetic data are often unavailable, requiring derivation of barrier-specific parameters primarily from new approach methodologies (NAMs), including in vitro, ex vivo, and in silico approaches. Their integration into PBK models depends on appropriate in vitro-to-in vivo extrapolation (IVIVE) methods that translate experimental kinetic observations into physiologically meaningful model parameters. Current parameterisation approaches are reviewed and critically evaluated. For placental transfer, ex vivo perfusion studies, trophoblast-based assays, and gestational physiology are integrated to estimate passive diffusion, active transport, and maternal-foetal exchange. For the BBB, advanced in vitro barrier models, quantitative transporter data, permeability–surface area scaling, and computational predictions support estimation of developmental brain exposure. For lactational transfer, PBK models incorporating physicochemical properties, maternal physiology, milk composition, and infant feeding patterns are used to estimate chemical partitioning into milk and postnatal exposure via breastfeeding. Across all three barriers, significant uncertainties remain regarding quantitative transporter ontogeny, metabolic activity, IVIVE methodologies, and independent evaluation of model predictions. Harmonised parameterisation workflows, transparent reporting, and machine-readable documentation are therefore essential to improve reproducibility, facilitate regulatory evaluation and strengthen the scientific robustness and regulatory application of PBK models for assessing early-life chemical exposure within NGRA.