Physiologically based Pharmacokinetic Modeling of Nicotine from Inhaled Aqueous Aerosol Predicts Marked Gastrointestinal Absorption in Rats

Authored by  AR Kolli, F Martin, Y Xiang, B Titz, E T Wong, W Schlage, E Veljkovic, P Vanscheeuwijck, J Hoeng

Presented at ASCPT 2019    

BACKGROUND: Pharmacokinetics (PK) of inhaled aerosol depends on the deposition fraction, the extent and rate of absorption in the aerodigestive tract, and pulmonary absorption, systemic distribution, and clearance. Our objective was to describe the absorption and disposition characteristics of inhaled nicotine-containing aerosol in rats.

METHOD: As per OECD guidelines for subacute inhalation toxicity testing, 12 male Sprague-Dawley rats per group were exposed (nose-only) to formulations containing 23 µg/L and 50 µg/L concentrations of nicotine for six hours/day, five days/week, for two weeks. The plasma concentrations of nicotine and cotinine were monitored 16 hours post-exposure on Days 4 and 11. We built a physiologically based PK (PBPK) model for inhaled formulations in R using the mrgsolve package [1] and parameters from Plowchalk et al. [2]. The fraction of aerosol entering the lung and gastrointestinal tract (GI), absorption rate from the GI (kGI), nicotine metabolism, and cotinine elimination were fitted using the global optimization package GenSA [3] to plasma concentrations.

RESULTS: The plasma time course of nicotine and cotinine showed no difference after two weeks of exposure and were well described by the PBPK model. The Cmax for nicotine was 620.5 ng/mL and 1400.9 ng/mL for 23 µg/L and 50 µg/L exposures, respectively. Only 66% of aerosol was absorbed through the lungs, and 34% was absorbed through the GI at a kGI of 1.19×10-3 hr-1. Nicotine halflife was 1.41 hr-1 even after marked GI absorption.

CONCLUSION: The model predicts systemic exposures for inhaled aerosols by estimating fractions deposited in the lung and GI. It can guide formulation of aerosols, and when adapted to humans, it could predict PK of inhaled aerosols in population.

A.R.Kolli_2019_Physiologically based Pharmacokinetic Modeling of Inhaled Aerosol Predicts Marked_