The human toxicological risk assessment of per- and polyfluoroalkyl substances (PFAS) is challenging, due to their sheer number and structural diversity, but also the paucity of the toxicity data required to characterize them. The development of Next Generation Physiologically Based Kinetic (NG-PBK) models may assist in overcoming this challenge. The mechanistic nature of NG-PBK models allows for their extrapolation from data-rich PFAS, such as perfluorooctanoic acid (PFOA), to data-poor ones, facilitating their application in Next Generation Risk Assessment (NGRA). The present study proposes a NG-PBK model for PFOA in humans, parametrized exclusively using in vitro-, and in silico- derived data. The model describes the toxicokinetic processes of 1) partitioning to plasma and tissue proteins, 2) partitioning to cell membrane lipids, 3a) transporter-mediated entero-hepatic circulation and 3b) renal elimination and reabsorption, and 4) elimination via menstruation. Global sensitivity analysis indicated that the model was most sensitive to the fraction unbound in plasma, active-transport parameters, and tissue-plasma partition coefficients. The model was equivalent to already available validated human PFOA-PBK models, while compared to those, it is not calibrated to observed animal, nor human data, illustrating its strength in being mechanistic. The serum concentrations and half-lives predicted by the NG-PBK model were within the ranges of those reported in human volunteer and biomonitoring (HBM) studies, demonstrating the model’s capacity to accurately predict PFOA toxicokinetics on exposure estimates. Extrapolation of the NG-PBK model to other PFAS, in conjunction with its integration with HBM data, will facilitate the NGRA of PFAS. This is particularly relevant given the paucity of in vivo data for most PFAS, ensuring compliance with the 3R principles. • A NG-PBK model can accurately predict the toxicokinetics of PFOA in humans. • Fraction unbound in plasma, active transport and tissue-plasma partition coefficients are the critical parameters of the model. • Age, serum albumin concentration and menstruation can in part explain the inter-individual variability in observed PFOA half-live.
Pachoulide et al. (Sun,) studied this question.