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Related Experiment Videos

Evaluation of an accelerated Caco-2 cell permeability model.

E Liang1, K Chessic, M Yazdanian

  • 1Pharmaceutics Department, Boehringer Ingelheim Pharmaceuticals, Inc., 900 Ridgebury Road, P.O. Box 368, Ridgefield, Connecticut 06877, USA.

Journal of Pharmaceutical Sciences
|March 9, 2000
PubMed
Summary

An accelerated Caco-2 cell permeability model offers faster drug screening. While it shows higher permeability and less P-glycoprotein expression, it maintains compound rank order, making it suitable for high-throughput screening.

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Area of Science:

  • Pharmacology
  • Cell Biology
  • Drug Discovery

Background:

  • Caco-2 cell monolayers are widely used to predict drug absorption.
  • Traditional Caco-2 permeability models require 21-25 days for monolayer development.
  • Accelerated models aim to reduce assay time and increase efficiency.

Purpose of the Study:

  • To evaluate an accelerated 3-7-day Caco-2 cell permeability model.
  • To compare its performance against the traditional 21-25-day model.
  • To assess its suitability for drug discovery and high-throughput screening.

Main Methods:

  • Comparison of Caco-2 cell permeability coefficients (P(Caco-2)) for 33 compounds.
  • Microscopy and transepithelial electrical resistance (TEER) measurements.

Related Experiment Videos

  • Assessment of P-glycoprotein expression and permeability directional ratios.

    • Main Results:

    • Accelerated model showed P(Caco-2) approximately twice that of the traditional model.
    • Reduced monolayer confluency and differentiation observed in the accelerated model.
    • No significant difference in the rank ordering of compound permeability.
    • Significantly lower P-glycoprotein expression and altered permeability ratios for efflux pump substrates in the accelerated model.

    Conclusions:

    • The accelerated Caco-2 model is not ideal for studying efflux pumps like P-glycoprotein.
    • It is a feasible alternative for rank ordering compounds in early drug discovery.
    • The model significantly improves turnover time and labor efficiency for high-throughput screening.