Drug-permeability and transporter assays in Caco-2 and MDCK cell lines

Donna A Volpe1

  • 1Food & Drug Administration, Center for Drug Evaluation & Research, 10903 New Hampshire Ave. Silver Spring, MD 20993-0002, USA. donna.volpe@fda.hhs.gov

Future Medicinal Chemistry
|November 22, 2011
PubMed

Insights

Caco-2 and Madin-Darby canine kidney cells are vital in vitro models for predicting drug absorption and interactions. Recent advancements enhance their utility in pharmaceutical research for better drug development.

Area of Science:

  • Pharmacology
  • Cell Biology
  • Drug Development

Background:

  • Caco-2 and Madin-Darby canine kidney (MDCK) cells are established in vitro models.
  • These cell lines form confluent monolayers on semiporous filters, mimicking the intestinal epithelial barrier.
  • They are crucial for assessing drug permeability and transporter interactions.

Purpose of the Study:

  • To review recent advancements in Caco-2 and MDCK cell-based assays for drug permeability.
  • To highlight applications in predicting drug absorption, transporter mechanisms, and drug-drug interactions.
  • To discuss innovative assay formats for improved in silico prediction.

Main Methods:

  • Utilizing Caco-2 and MDCK cell monolayers cultured on semiporous filters.
  • Employing assays to evaluate drug permeability and transporter interactions.
  • Reviewing studies involving transfected/knock-down cells, miniaturization, automation, and assay combinations.

Main Results:

  • These assays enable qualitative prediction and ranking of drug absorption.
  • They help elucidate mechanisms of drug permeability and formulation effects.
  • Recent innovations improve the prediction of transporter-mediated drug-drug interactions.

Conclusions:

  • Caco-2 and MDCK cell assays are indispensable tools in pharmaceutical research and development.
  • Advancements in assay technology enhance the understanding and prediction of intestinal drug absorption.
  • These models are critical for optimizing drug candidates and predicting in vivo behavior.

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