1,640
Views
101
CrossRef citations to date
0
Altmetric
Reviews

Cell-based in vitro models for predicting drug permeability

, , , , &
Pages 607-621 | Published online: 18 Mar 2012
 

Abstract

Introduction: In vitro cell models have been used to predict drug permeation in early stages of drug development, since they represent an easy and reproducible method, allowing the tracking of drug absorption rate and mechanism, with an advantageous cost–benefit ratio. Such cell-based models are mainly composed of immortalized cells with an intrinsic ability to grow in a monolayer when seeded in permeable supports, maintaining their physiologic characteristics regarding epithelium cell physiology and functionality.

Areas covered: This review summarizes the most important intestinal, pulmonary, nasal, vaginal, rectal, ocular and skin cell-based in vitro models for predicting the permeability of drugs. Moreover, the similitude between in vitro cell models and in vivo conditions are discussed, providing evidence that each model may provisionally resemble different drug absorption route.

Expert opinion: Despite the widespread use of in vitro cell models for drug permeability and absorption evaluation purposes, a detailed study on the properties of these models and their in vitro–in vivo correlation compared with human data are required to further use in order to consider a future drug discovery optimization and clinical development.

Notes

This box summarizes key points contained in the article.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 99.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 727.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.