Re-defining kinetic lung overload: Time for new paradigms.

Area of Science:

• Toxicology
• Inhalation Toxicology
• Particle Toxicology

Background:

• Poorly soluble, low-toxicity particles (PSLTs) can cause lung overload, impacting toxicological assessments.
• Understanding the key metrics of kinetic lung overload is crucial for accurate risk assessment.
• Previous studies often focused on particle characteristics without a unifying overload metric.

Purpose of the Study:

• To identify a unifying key metric for kinetic lung overload in rats exposed to different PSLTs.
• To compare the impact of particle density on lung overload endpoints.
• To develop a kinetic modeling approach for predicting no observed adverse effect concentration (NOAEC) and maximum tolerated dose (MTD).

Main Methods:

• Comparative analysis of 13-week inhalation studies using Multi-Walled Carbon Nanotubes (MWCNT) and black iron oxide (Fe3O4).
• Analysis of bronchoalveolar lavage (BAL) cell counts and corpuscular volumes.
• Kinetic modeling to interrelate cumulative lung burdens with elimination half-times and adverse effects.

Main Results:

• An increased pool-size of BAL cells, rather than increased cell volume, is the primary adverse outcome pathway indicator for lung overload.
• The increased BAL cell pool size is directly related to the prolonged elimination half-time of PSLTs.
• Kinetic modeling successfully predicted NOAEC and MTD for PSLT inhalation studies.

Conclusions:

• Kinetic modeling provides a versatile tool for predicting key outcomes in repeated inhalation studies with PSLTs.
• This approach allows for the harmonization of studies with different PSLTs and facilitates AOP-facilitated read-across.
• Risk assessors can better distinguish between generic lung overload and substance-specific pathologies.