A new approach to modeling transdermal ethanol kinetics.

Area of Science:

• Physiology
• Pharmacokinetics
• Biomedical Engineering

Background:

• Supradermal alcohol concentration (SAC) measurement is a non-invasive method for monitoring blood alcohol concentration (BAC).
• Previous models describing the relationship between SAC and BAC utilized partial and ordinary differential equations (PDE model).
• The existing PDE model accurately predicted experimental SAC measures across various BAC profiles.

Purpose of the Study:

• To develop and validate a new, simplified mathematical model for transdermal ethanol kinetics.
• To utilize ordinary differential equations (ODE model) and a mass transfer coefficient for modeling ethanol movement through the skin.
• To compare the performance of the new ODE model against the established PDE model.

Main Methods:

• A novel ODE model was formulated using a mass transfer coefficient to describe transdermal ethanol kinetics.
• The ODE model was evaluated using diverse blood alcohol concentration (BAC) profiles, varying absorption times and peak concentrations.
• Sensitivity analysis was performed on the ODE model, examining factors like stratum corneum properties and gas volume above the skin.

Main Results:

• The ODE model demonstrated performance comparable to the existing PDE model in predicting supradermal alcohol concentration (SAC).
• The ODE model exhibited slightly slower washout rates and delayed times to peak SAC and return to zero SAC compared to the PDE model.
• Sensitivity analysis indicated that stratum corneum solubility, diffusivity, thickness, and overlying gas volume significantly influence ODE model performance.

Conclusions:

• The newly developed ODE model provides a robust and simplified approach to modeling transdermal ethanol kinetics.
• This ODE model offers advantages in streamlining integration with larger physiological models and reducing computational time.
• The model facilitates quicker conversion of skin alcohol measurements to blood alcohol concentrations, enhancing monitoring applications.