Novel in vitro model barriers for evaluation of the permeability of antitumor compounds, thioxanthones

Venugopal Marasanapalle1, Xiaoling Li, Lisa Polin

  • 1Department of Pharmaceutics & Medicinal Chemistry, TJ Long School of Pharmacy & Health Sciences, University of the Pacific, Stockton, CA 95211, USA.

Investigational New Drugs
|February 28, 2006
PubMed

Insights

This study used in vitro models to assess anticancer drug penetration barriers. Thioxanthone compounds showed high permeability, predicting good in vivo tissue distribution for improved tumor targeting.

Area of Science:

  • Pharmacology and Drug Delivery
  • Cancer Biology
  • Biomedical Engineering

Background:

  • Tumor micro-environments present penetration barriers to anticancer drugs, limiting efficacy.
  • Understanding drug permeability is crucial for effective cancer treatment.
  • In vitro models can simulate tumor barriers to predict drug behavior.

Purpose of the Study:

  • To evaluate the in vitro permeability of thioxanthone anticancer compounds.
  • To correlate in vitro permeability with in vivo drug distribution.
  • To validate the use of in vitro models for predicting drug tissue penetration.

Main Methods:

  • Utilized two in vitro model barriers: Matrigel for extracellular matrix and Caco-2 cell multilayers for tumor structure.
  • Assessed the permeability of four structurally related thioxanthone compounds across these barriers.
  • Correlated the measured apparent permeability coefficients with known in vivo distribution data.

Main Results:

  • Thioxanthone analogs exhibited apparent permeability coefficients ranging from 2.9 x 10(-6) to 11.8 x 10(-6) cm/s across Matrigel.
  • Permeability across Caco-2 multilayers ranged from 12.6 x 10(-6) to 24.5 x 10(-6) cm/s.
  • High in vitro permeability correlated with favorable in vivo tissue distribution.

Conclusions:

  • In vitro model barriers effectively simulate tumor penetration challenges.
  • The permeability of thioxanthones across these models predicts their in vivo distribution.
  • This approach offers a valuable tool for optimizing anticancer drug development.