Lung dosimetry and risk assessment of nanoparticles: evaluating and extending current models in rats and humans.

Abstract:

:Risk assessment of occupational exposure to nanomaterials is needed. Human data are limited, but quantitative data are available from rodent studies. To use these data in risk assessment, a scientifically reasonable approach for extrapolating the rodent data to humans is required. One approach is allometric adjustment for species differences in the relationship between airborne exposure and internal dose. Another approach is lung dosimetry modeling, which provides a biologically-based, mechanistic method to extrapolate doses from animals to humans. However, current mass-based lung dosimetry models may not fully account for differences in the clearance and translocation of nanoparticles. In this article, key steps in quantitative risk assessment are illustrated, using dose-response data in rats chronically exposed to either fine or ultrafine titanium dioxide (TiO2), carbon black (CB), or diesel exhaust particulate (DEP). The rat-based estimates of the working lifetime airborne concentrations associated with 0.1% excess risk of lung cancer are approximately 0.07 to 0.3 mg/m3 for ultrafine TiO2, CB, or DEP, and 0.7 to 1.3 mg/m3 for fine TiO2. Comparison of observed versus model-predicted lung burdens in rats shows that the dosimetry models predict reasonably well the retained mass lung burdens of fine or ultrafine poorly soluble particles in rats exposed by chronic inhalation. Additional model validation is needed for nanoparticles of varying characteristics, as well as extension of these models to include particle translocation to organs beyond the lungs. Such analyses would provide improved prediction of nanoparticle dose for risk assessment.

journal_name

Inhal Toxicol

journal_title

Inhalation toxicology

authors

Kuempel ED,Tran CL,Castranova V,Bailer AJ

doi

10.1080/08958370600747887

subject

Has Abstract

pub_date

2006-09-01 00:00:00

pages

717-24

issue

10

eissn

0895-8378

issn

1091-7691

pii

P0H7JM36186M0G60

journal_volume

18

pub_type

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