Predicting phenolic acid absorption in Caco-2 cells: a theoretical permeability model and mechanistic study

Area of Science:

• Pharmacokinetics and Drug Delivery
• Computational Chemistry and Molecular Modeling

Background:

• Rationalizing membrane permeability and transport mechanisms is crucial for developing potential nutraceuticals.
• Existing models often lack precision in predicting transcellular absorption across biological barriers like Caco-2 monolayers.

Purpose of the Study:

• To develop a theoretical permeability equation for calculating the transcellular absorption component across Caco-2 cell monolayers.
• To establish a predictive model for nutraceutical and drug absorption based on physicochemical properties.

Main Methods:

• Correlated published Caco-2 permeability data for 30 drugs with 1-octanol/water distribution coefficient (log D) and molecular mass.
• Utilized nonlinear regression analysis to derive model parameters (a', β', b') for the theoretical transcellular permeability (TTP) model.
• Validated the TTP model against experimental data for nine new compounds and applied it to predict phenolic acid absorption.

Main Results:

• The TTP model demonstrated a good fit with published data (R² = 0.93) and predicted independent data reasonably well (R² = 0.86).
• The model successfully predicted the absorption characteristics of six phenolic acids.
• In vitro studies indicated that deviations from predicted transcellular permeability may involve active uptake, efflux transporters, or paracellular flux.

Conclusions:

• The developed TTP model provides a valuable tool for predicting the transcellular absorption of compounds.
• Understanding deviations from predicted permeability is essential for elucidating complex transport mechanisms.
• This approach aids in the rational design and development of nutraceuticals and drugs with improved absorption profiles.