Nicotine and cotinine exposure from electronic cigarettes: a population approach

Abstract

Background and objectives: Electronic cigarettes (e-cigarettes) are a recent technology that has gained rapid acceptance. Still, little is known about them in terms of safety and effectiveness. A basic question is how effectively they deliver nicotine; however, the literature is surprisingly unclear on this point. Here, a population pharmacokinetic model was developed for nicotine and its major metabolite cotinine with the aim to provide a reliable framework for the simulation of nicotine and cotinine concentrations over time, based solely on inhalation airflow recordings and individual covariates [i.e., weight and breath carbon monoxide (CO) levels].

Methods: This study included ten adults self-identified as heavy smokers (at least one pack of cigarettes per day). Plasma nicotine and cotinine concentrations were measured at regular 10-min intervals for 90 min while human subjects inhaled nicotine vapor from a modified e-cigarette. Airflow measurements were recorded every 200 ms throughout the session. A population pharmacokinetic model for nicotine and cotinine was developed based on previously published pharmacokinetic parameters and the airflow recordings. All of the analyses were performed with the non-linear mixed-effect modeling software NONMEM(®) version 7.2.

Results: The results show that e-cigarettes deliver nicotine effectively, although the pharmacokinetic profiles are lower than those achieved with regular cigarettes. Our pharmacokinetic model effectively predicts plasma nicotine and cotinine concentrations from the inhalation volume, and initial breath CO.

Conclusion: E-cigarettes are effective at delivering nicotine. This new pharmacokinetic model of e-cigarette usage might be used for pharmacodynamic analysis where the pharmacokinetic profiles are not available.

Figures

Figure 1. Diagram of custom e-cigarette apparatus

Air passed through a ceramic heater encased in 2” diameter PVC pipe, where it was heated to a controlled temperature of 300F. The heated air passed through a small orifice and over a ½” diameter ball of non-ferromagnetic metallic wool, which was saturated with 0.45mL of smoke juice (Johnson Creek, nominal 18 mg/mL nicotine). The resulting heated vapor passed through a one-way check valve along a 12” section of flexible tubing and into the user's mouth. Inhaled airflow was measured in mL/min.

Figure 2. A. Airflow: Raw data. B. Airflow: Processed data

The processing was developed in three consecutive steps: (i) Every negative value was transformed to zero; (ii) the 97.5th percentile was calculated based on all subjects; (iii) Every value below such percentile was transformed to zero. C. Airflow: Dose events. The dose events and their intensities were defined as processed airflow recordings bigger than zero (see methods for more details).

Figure 3

A. Individual dose events identified from the airflow Every subplot corresponds a different individual. Circles represent the dose events, the individual is inhaling, based on the airflow measurements. B. Individual nicotine plasma concentrations. Circles are the observed nicotineconcentrations for every individual. Dashed lines are a linear interpolation between the observations. Solid black line shows the observed median kinetic for nicotine. Every color corresponds to a different individual. Same color code was used than for the individual dose events subplots, allowing the connection between airflow – dose events and the nicotine PK profiles.

Figure 4. Structural pharmacokinetic model for nicotine and its major metabolite cotinine

Circles represent the central compartments for nicotine and cotinine. PK parameters: F, scaling factor for dose calculation and bioavailability; VC and VM are the volumes of distribution of the central compartment for nicotine and cotinine respectively, CL2COT and CL2METO are the formation rates for cotinine and other metabolites respectively; CLEX and CLCOT are the elimination rates for nicotine and cotinine.

Figure 5. Individual predictions versus observations for nicotine (A) and cotinine (B)

The grey colors in (A) denote nicotine; and the light blue colors in (B) denote cotinine. Circles represent observations above the minimum quantification level. Squares represent observations below the quantification level. The red dashed lines represent the population prediction. The solid lines represent the individual predictions.

Figure 6

Goodness of fit plots of the selected population PK model for (A) nicotine (grey) and (B) cotinine (light blue). PRED corresponds to the population model predictions, IPRED to the individual model predictions and NPDE the normalized prediction distribution errors. Solid lines show the identity lines for the first two columns and 0 line for the last column.

Figure 7. Individual Visual Predictive Checks

Results from 200 simulated studies. Shaded areas represent the 95% prediction interval (PI) for every individual based on their airflow, CO levels and weight. The black lines correspond to the median of the simulated subjects. Points are the observations. The grey color stands for nicotine (A) and light blue for the major metabolite cotinine (B).