Optimizing the use of ultrasound to deliver chemotherapeutic agents to cancer cells from polymeric micelles

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

Research output: Contribution to journalArticle

14 Citations (Scopus)

Abstract

In this study, we present an artificial neural network (ANN) model that attempts to predict the dynamic release of doxorubicin (Dox) from P105 micelles under different ultrasonic power densities at 20 kHz. The goal is to utilize the developed ANN model in optimizing the ultrasound application to achieve a target drug release at the tumor site by controlling power density and ultrasound duration via an ANN-based model predictive control. The parameters of the controller are then tuned to achieve good reference signal tracking.

Original languageEnglish
Pages (from-to)1276-1284
Number of pages9
JournalJournal of the Franklin Institute
Volume348
Issue number7
DOIs
Publication statusPublished - Sep 2011

Fingerprint

Micelles
Ultrasound
Artificial Neural Network
Cancer
Ultrasonics
Cells
Neural networks
Neural Network Model
Cell
Model predictive control
Model Predictive Control
Tumors
Tumor
Drugs
Controller
Predict
Controllers
Target

Keywords

  • Doxorubicin
  • Drug release
  • NN-MPC
  • P105 micelles
  • Ultrasound stimulation

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Networks and Communications
  • Applied Mathematics
  • Signal Processing

Cite this

Optimizing the use of ultrasound to deliver chemotherapeutic agents to cancer cells from polymeric micelles. / Husseini, Ghaleb A.; Abdel-Jabbar, Nabil M.; Mjalli, Farouq S.; Pitt, William G.; Al-Mousa, Ala'A.

In: Journal of the Franklin Institute, Vol. 348, No. 7, 09.2011, p. 1276-1284.

Research output: Contribution to journalArticle

Husseini, Ghaleb A. ; Abdel-Jabbar, Nabil M. ; Mjalli, Farouq S. ; Pitt, William G. ; Al-Mousa, Ala'A. / Optimizing the use of ultrasound to deliver chemotherapeutic agents to cancer cells from polymeric micelles. In: Journal of the Franklin Institute. 2011 ; Vol. 348, No. 7. pp. 1276-1284.
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