Nanoparticle encapsulation and controlled release of a hydrophobic kinase inhibitor: Three stage mathematical modeling and parametric analysis

Armando Lucero-Acuña, Roberto Guzmán*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

24 Scopus citations

Abstract

A mathematical model of drug release that incorporates the simultaneous contributions of initial burst, nanoparticle degradation-relaxation and diffusion was developed and used to effectively describe the release of a kinase inhibitor and anticancer drug, PHT-427. The encapsulation of this drug into PLGA nanoparticles was performed by following the single emulsion-solvent evaporation technique and the release was determined in phosphate buffer pH 7.4 at 37 °C. The size of nanoparticles was obtained in a range of 162-254 nm. The experimental release profiles showed three well defined phases: an initial fast drug release, followed by a nanoparticle degradation-relaxation slower release and then a diffusion release phase. The effects of the controlled release most relevant parameters such as drug diffusivity, initial burst constant, nanoparticle degradation-relaxation constant, and the time to achieve a maximum rate of drug release were evaluated by a parametrical analysis. The theoretical release studies were corroborated experimentally by evaluating the cytotoxicity effectiveness of the inhibitor AKT/PDK1 loaded nanoparticles over BxPC-3 pancreatic cancer cells in vitro. These studies show that the encapsulated inhibitor AKT/PDK1 in the nanoparticles is more accessible and thus more effective when compared with the drug alone, indicating their potential use in chemotherapeutic applications.

Original languageEnglish
Article number15053
Pages (from-to)249-257
Number of pages9
JournalInternational Journal of Pharmaceutics
Volume494
Issue number1
DOIs
StatePublished - 15 Oct 2015

Bibliographical note

Publisher Copyright:
© 2015 Elsevier B.V.

Keywords

  • Controlled release
  • Mathematical modeling
  • Nanoparticles
  • PLGA
  • Pancreatic cancer
  • Parametric analysis

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