Related Experiment Video
Updated: Jan 8, 2026

Modeling Fast-scan Cyclic Voltammetry Data from Electrically Stimulated Dopamine Neurotransmission Data Using QNsim1.0
Published on: June 5, 2017
Development of a Physiologically Based Pharmacokinetic (PBPK) Simulation Model for Nicotine
Brian Kim1, Sung Hun Bae1, Mohamed Bashar1
1School of Pharmacy and Pharmaceutical Sciences, Binghamton University, State University of New York, Binghamton, New York, USA.
None:
Tobacco is a major cause of chronic diseases such as lung cancer, cardiovascular disease, and chronic obstructive pulmonary disease worldwide. Nicotine, the primary psychoactive component in tobacco, is highly addictive and while not the primary driver of such tobacco-related diseases, poses various health risks, particularly those affecting the cardiovascular and pulmonary systems. Although nicotine-based therapies, such as nicotine replacement products, are widely utilized in smoking cessation efforts today, the impact of newer, tobacco delivery systems such as electronic nicotine delivery systems, or ENDS, remains uncertain and warrants continued evaluation. This study aims to develop and validate a physiologically based pharmacokinetic (PBPK) simulation model for nicotine using clinical pharmacokinetic data. The PBPK simulation model for nicotine was developed by incorporating drug-specific and system-specific parameters and by considering the systemic absorption, distribution, metabolism, and excretion of nicotine as well as its overall pharmacokinetic behavior on GastroPlus version 9.9. Validation of the developed PBPK model was performed by comparing predicted and observed plasma concentration-time profiles and pharmacokinetic parameters from clinical studies across multiple routes of administration including intravenous infusion, bolus, and pulmonary inhalation. The resulting model accurately captured plasma nicotine concentrations, with predicted pharmacokinetic parameters (Cmax, Tmax and AUCs) falling within acceptable ranges of observed values and computational average fold error values. The current model provides a practical tool to translate systemic nicotine exposure across delivery systems, support dose optimization against predefined target exposure, and quantify safety margins, thereby informing safer product design and evidence-based decisions in public-health regulatory science.
More Related Videos
08:47Spectral Confocal Imaging of Fluorescently tagged Nicotinic Receptors in Knock-in Mice with Chronic Nicotine Administration
Published on: February 10, 2012
09:50Impact Assessment of Repeated Exposure of Organotypic 3D Bronchial and Nasal Tissue Culture Models to Whole Cigarette Smoke
Published on: February 12, 2015
Related Concept Videos
Pharmacokinetic Models: Overview
There are three primary types of models: empirical, compartment, and physiological. Empirical models, with minimal...
Pharmacokinetic Models: Comparison and Selection Criterion
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
Model Approaches for Pharmacokinetic Data: Physiological Models
Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models
Physiological Pharmacokinetic Models: Incorporating Hepatic Transporter-Mediated Clearance
A recent model describes pravastatin's hepatobiliary excretion,...
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...