Nicotine Population Pharmacokinetics in Healthy Adult Smokers: A Retrospective Analysis

Abstract

Background and objective: Characterizing nicotine pharmacokinetics is challenging in the presence of background exposure. We performed a combined retrospective population pharmacokinetic analysis of 8 trials, including exposure to Tobacco Heating System and cigarettes (both inhaled), nicotine nasal spray and oral nicotine gum.

Method: Data from 4 single product use trials were used to develop a population pharmacokinetic model with Phoenix^® NLME™ and to derive exposure parameters. Data from 4 separate ad libitum use studies were used for external validation. A total of 702 healthy adult smokers (54% males; 21-66 years of age; smoking ≥10 cigarettes/day; from US, Europe and Japan) were eligible for participation.

Results: Two-compartment linear disposition combined with zero-order absorption model was adequate to describe nicotine pharmacokinetics, and a mono-exponentially decreasing background component was utilized to account for nicotine carry-over effects. Apparent nicotine clearance was typically 0.407 L/min in males and 26% higher in females (68% inter-individual variability). Bioavailability was product-specific, decreased with increasing nicotine ISO yield, and increased with increasing body weight. Absorption duration was apparently prolonged with nicotine gum. The typical initial and terminal half-lives were 1.35 and 17 h, respectively. The presence of menthol did not impact the determinants of the area under the curve. The model adequately described the external validation data.

Conclusions: The population model was able to describe in different populations the nicotine pharmacokinetics after single product use and after 4 days of ad libitum use of Tobacco Heating System, cigarettes, and of different nicotine replacement therapies with various routes of administration.

Fig. 1

Population pharmacokinetic analysis workflow. After omitting measurements below the level of quantification (BLQ) and splitting the full dataset into learning and validation datasets, an exploratory data analysis (EDA) was conducted to guide data cleaning and base model development. The covariate model (COV1) was developed sequentially after defining a hierarchy between primary and secondary covariates, until a final model was obtained. Sensitivity analyses assessed the impact of outlier data on the base model. Model evaluation was performed on the base and final models, including goodness-of-fit (GOF) plots. The final model was submitted to external evaluation using the validation dataset, and visual predictive check (VPC). Eventually, individual exposure metrics were derived from the learning dataset

Fig. 2

Compartmental representation and equations defining the structural model of nicotine prior to inclusion of covariates. A1 nicotine amount in the central compartment, A2 nicotine amount in the peripheral compartment, Bckgrd model-predicted background nicotine concentration, alpha initial rate constant, beta terminal rate constant, C1 model-predicted concentration in the central compartment, C0 baseline nicotine concentration prior to first product use, C2 nicotine concentration in the peripheral compartment, Cl/F apparent clearance, Cl2/F apparent inter-compartmental clearance, Ctotal model-predicted total nicotine concentration, k10 microscopic elimination rate constant, k12 microscopic rate constant for the transfer from the central to the peripheral compartment, k21 microscopic rate constant for the transfer from the peripheral to the central compartment, Tdur duration of zero-order absorption, V1/F apparent central volume of distribution, V2/F apparent peripheral volume of distribution

Fig. 3

Visual predictive check of the Final Model–Semi-log Scale (learning dataset). CC conventional cigarette, NNS nicotine nasal spray, PI prediction interval, THS tobacco heating system. Given the small number of measurements at 24 h, simulations were not displayed beyond 12 h for NNS and gum