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dc.contributor.authorHusseini, Ghaleb
dc.contributor.authorAbdel-Jabbar, Nabil
dc.contributor.authorMjalli, Farouq Sabri
dc.contributor.authorPitt, William G.
dc.date.accessioned2021-03-07T09:27:16Z
dc.date.available2021-03-07T09:27:16Z
dc.date.issued2007
dc.identifier.citationHusseini GA, Abdel-Jabbar NM, Mjalli FS, Pitt WG. Modeling and Sensitivity Analysis of Acoustic Release of Doxorubicin from Unstabilized Pluronic P105 Using an Artificial Neural Network Model. Technology in Cancer Research & Treatment. February 2007:49-56. doi:10.1177/153303460700600107.en_US
dc.identifier.issn1533-0346
dc.identifier.urihttp://hdl.handle.net/11073/21348
dc.description.abstractThis 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.en_US
dc.language.isoen_USen_US
dc.publisherAdenine Pressen_US
dc.relation.urihttps://doi.org/10.1177/153303460700600107en_US
dc.subjectArtificial neural networksen_US
dc.subjectPolymeric micellesen_US
dc.subjectUltrasonic stimulusen_US
dc.subjectDoxorubicinen_US
dc.subjectPluronic P105en_US
dc.titleModeling and Sensitivity Analysis of Acoustic Release of Doxorubicin from Unstabilized Pluronic P105 Using an Artificial Neural Network Modelen_US
dc.typePeer-Revieweden_US
dc.typeArticleen_US
dc.typePublished versionen_US
dc.identifier.doi10.1177/153303460700600107


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