Physiologically based pharmacokinetic modeling of metal nanoparticles for risk assessment of inhalation exposures: a state-of-the-science expert panel review.

Kirman, C. R.; Kent, B.; Bigelow, J.; Canady, R. A.; Chen, Q.; Chou, W. C.; Li, D.; Lin, Z.; Kumar, V.; Paini, A.; Poulin, P.; Sweeney, L. M.; Hays, S. M.

A critical review of the current state-of-the-science for the physiologically based pharmacokinetic (PBPK) modeling of metal nanoparticles and their application to human health risk assessment for inhalation exposures was conducted. A systematic literature search was used to identify four model groups (defined as a primary publication along with multiple supplementary publications) subject to review. Using a recent guideline document from the Organization for Economic Cooperation and Development (OECD) for PBPK model evaluation, these model groups were critically peer-reviewed by an independent panel of experts to identify those to be considered for modeling and simulation application. Based upon the expert panel input, model confidence scores for the four model groups ranged from 30 to 41 (out of a maximum score of 50). The three highest-scoring model groups were then applied to compare predictions to a different metal nanoparticle (i.e. not specifically used to parameterize the original models) using a recently published data set for tissue burdens in rats, as well as predicting human tissue burdens expected for corresponding occupational exposures. Overall, the rat models performed reasonably well in predicting the lung but tended to overestimate systemic tissue burdens. Data needs for improving the state-of-the-science, including quantitative particle characterization in tissues, nanoparticle-corona data, long-term exposure data, interspecies extrapolation methods, and human biomonitoring/toxicokinetic data are discussed.

LABORATORY rats; HEALTH risk assessment; METAL nanoparticles; NANOPARTICLES; CRITICAL currents

Nanotoxicology, 2024, Vol 18, Issue 6, p527

1743-5390

Academic Journal

10.1080/17435390.2024.2401430