A Benchtop Round Window Model for Studying Magnetic Nanoparticle Transport to the Inner Ear

IntroductionThe round window membrane (RWM) presents a significant barrier to the local application of therapeutics to the inner ear. We demonstrate a benchtop preclinical RWM model and evaluate superparamagnetic iron oxide nanoparticles (SPIONs) as vehicles for magnetically assisted drug delivery.MethodsGuinea pig RWM explants were inset into a 3D-printed dual chamber benchtop device. Custom-synthesized 7-nm iron core nanoparticles were modified with different polyethylene glycol chains to yield two sizes of SPIONs (NP-PEG600 and NP-PEG3000) and applied to the benchtop model with and without a magnetic field. Histologic analysis of the RWM was performed using transmission electron microscopy (TEM) and confocal microscopy.ResultsOver a 4-h period, 19.5 +/- 1.9% of NP-PEG3000 and 14.6 +/- 1.9% of NP-PEG600 were transported across the guinea pig RWM. The overall transport increased by 1.45x to 28.4 +/- 5.8% and 21.0 +/- 2.0%, respectively, when a magnetic field was applied. Paraformaldehyde fixation of the RWM decreased transport significantly (NP-PEG3000: 7.6 +/- 1.5%; NP-PEG600: 7.0 +/- 1.6%). Confocal and electron microscopy analysis demonstrated nanoparticle localization throughout all cellular layers and layer-specific transport characteristics within RWM.ConclusionThe guinea pig RWM explant benchtop model allows for targeted and practical investigations of transmembrane transport in the development of nanoparticle drug delivery vehicles. The presence of a magnetic field increases SPION delivery by 45%-50% in a nanoparticle size- and cellular layer-dependent manner.Level of EvidenceNA Laryngoscope, 2024 We designed a benchtop model for investigating transport mechanics of magnetic nanoparticles across the round window membrane. Delivery of these particles increases by 40% with application of an external magnetic field gradient, and the mechanism of transport across the membrane appears to be mediated by active cellular processes. image