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Updated: Dec 31, 2025

Development of a Preclinical Inhalation Model to Test Vaporized Cannabis Distillates
Published on: May 30, 2025
Bridging inhaled aerosol dosimetry to physiologically based pharmacokinetic modeling for toxicological assessment:
A R Kolli1, A K Kuczaj1,2, F Martin1
1PMI R&D, Philip Morris Products S.A, Neuchâtel, Switzerland.
Abstract:
One of the challenges for toxicological assessment of inhaled aerosols is to accurately predict their deposited and absorbed dose. Transport, evolution, and deposition of liquid aerosols are driven by complex processes dominated by convection-diffusion that depend on various factors related to physics and chemistry. These factors include the physicochemical properties of the pure substance of interest and associated mixtures, the physical and chemical properties of the aerosols generated, the interplay between different factors during transportation and deposition, and the subject-specific inhalation topography. Several inhalation-based physiologically based pharmacokinetic (PBPK) models have been developed, but the applicability of these models for aerosols has yet to be verified. Nicotine is among several substances that are often delivered via the pulmonary route, with varied kinetics depending upon the route of exposure. This was used as an opportunity to review and discuss the current knowledge and state-of-the-art tools combining aerosol dosimetry predictions with PBPK modeling efforts. A validated tool could then be used to perform for toxicological assessment of other inhaled therapeutic substances. The Science Panel from the Alliance of Risk Assessment have convened at the "Beyond Science and Decisions: From Problem Formulation to Dose-Response Assessment" workshop to evaluate modeling approaches and address derivation of exposure-internal dose estimations for inhaled aerosols containing nicotine or other substances. The discussion involved PBPK model evaluation criteria, challenges, and choices that arise in such a model design, development, and application as a computational tool for use in human toxicological assessments.
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