Synthesis of drug carrier smart ferrogels and application of artificial neural network in modeling their doxorubicin release behavior under alternating magnetic fields

Abstract

AbstractThe development of magnetic field‐sensitive smart drug delivery systems with superior properties has become an area of increasing academic and industrial importance. In this study, smart poly(NIPAAm‐co‐VSA)‐rGO/Fe3O4 ferrogels with varying concentrations of reduced graphene oxide (rGO) were synthesized. Fe3O4 nanoparticles loaded ferrogels were obtained by the in situ reduction of Fe ions. The morphologic, structural, and magnetic properties of ferrogel systems were characterized. Doxorubicin (DOX) was loaded to the synthesized ferrogels by solution impregnation method and their heating and drug release behavior over time under alternating magnetic field AMFs of 1.37, 1.64, and 1.91 millitesla (mT) were investigated. The drug loading and releasing characteristics of the ferrogel series were calculated. When the experimental results were examined, it was determined that the amount of rGO in the structure of the developed ferrogel systems had a very high effect on the magnetic, heating, and drug loading‐release characteristics of the ferrogels. To modeling their multivariable DOX release behavior, artificial neural network modeling technique was used. Calculated model performance parameters have shown that this developed artificial intelligence technique has great success in modeling complex and nonlinear DOX release behaviors.