Magnetically Responsive Polymer Colloids of Cobalt Ferrites Nanoparticles for Theranostic Applications

Abstract

There are extensive research efforts being carried out to develop next generation theranostic smart materials and their employment for elaborative biomedical applications including combination of both therapy and diagnostics. Enhancement in the functionalities of the colloids and their application in biomedical theranostic is latest area of interest. In view of above, present project aims to develop the magnetically responsive polymers colloids for theranostic applications. Magnetic nanoparticles of CoFe2O4 were synthesized using co-precipitation method by iron nitrate (Fe (NO3)3.9H2O) and cobalt nitrite (CO (NO3)2 .6H2O) salts in NaOH as precipitating agent. Particles were acid treated and characterized. Magnetically responsive polymer colloids were also synthesized by single emulsion solvent evaporation technique. Organic phase contained Methotrexate (MTX) drug, Eudagrit E100 and CoFe2O4 in ethanol whereas, aqueous phase contained polysorbate in deionized water. Optimization technique was employed to get stable emulsion by varying concentration of Methotrexate, Eudagrit and CoFe2O4 , total of 40 formulations, 20 each HNO3 treated untreated CoFe2O4, were produced at sonication amplitude of 60% at 20 kHz. After centrifugation at 13,000 rpm and lypholization at -76 oC at 0.014 mbar, the prepared magnetic polymer colloids were thoroughly characterized for their sizes, sizes distribution, surface charges, magnetic properties, morphology and composition. To determine the therapeutic potential of the prepared emulsion drug release experiment was carried out. Total encapsulated MTX content in the optimized emulsion was 55%. Dissolution was observed for up to 48 hours and total 8 samples were collected at fixed time interval for nanoparticles of iron cobalt coated eudagrit e 100 polymers which corresponds to 90 % drug release. In order to determine kinetics of the drug release different models such as zero order, first order, Higuchi, Hixen Crowell and korsemeyer Peppas models. Best fit model has been chosen on the basis of correlation coefficient (R2) i.e. Hixon Crowell model. The developed project has significant potential in biomedical diagnostic and therapeutic applications in future.