Modeling and sensitivity analysis of acoustic release of boxorubicin from unstabilized pluronic P105 using an artificial neural network model

Ghaleb A. Husseini, Nabil M. Abdel-Jabbar, Farouq S. Mjalli, William G. Pitt

Research output: Contribution to journalArticle

35 Citations (Scopus)

Abstract

This paper models steady state acoustic release of Doxorubicin (Dox) from Pluronic P105 micelles using Artificial Neural Networks (ANN), Previously collected release data were compiled and used to train, validate, and test an ANN model. Sensitivity analysis was then performed on the following operating conditions: ultrasonic frequency, power density, Pluronic P105 concentration, and temperature. The model showed that drug release was most efficient at lower frequencies. The analysis also demonstrated that release increases as the power density increases. Sensitivity plots of ultrasound intensity revealed a drug release threshold of 0.015 W/cm2 and 0.38 W/cm2 at 20 and 70 kHz, respectively. The presence of a power density threshold provides strong evidence that cavitation plays an important role in acoustically activated drug release from polymeric micelles. Based on the developed model, Dox release is not a strong function of temperature, suggesting that thermal effects do not play a major role in the physical mechanism involved. Finally, sensitivity plots of P105 concentration indicated that higher release was observed at lower copolymer concentrations.

Original languageEnglish
Pages (from-to)49-56
Number of pages8
JournalTechnology in Cancer Research and Treatment
Volume6
Issue number1
Publication statusPublished - Feb 2007

Keywords

  • and Pluronic P105
  • Artificial neural networks
  • Doxorubicin
  • Polymeric micelles
  • Ultrasonic stimulus

ASJC Scopus subject areas

  • Cancer Research
  • Radiology Nuclear Medicine and imaging

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