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Issue 13, 2019
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Remotely controlled nanofluidic implantable platform for tunable drug delivery

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Chronic diseases such as hypertension and rheumatoid arthritis are persistent ailments that require personalized lifelong therapeutic management. However, the difficulty of adherence to strict dosing schedule compromises therapeutic efficacy and safety. Moreover, the conventional one-size-fits-all treatment approach is increasingly challenged due to the intricacies of inter- and intra-individual variabilities. While accelerated technological advances have led to sophisticated implantable drug delivery devices, flexibility in dosage and timing modulation to tailor precise treatment to individual needs remains an elusive goal. Here we describe the development of a subcutaneously implantable remote-controlled nanofluidic device capable of sustained drug release with adjustable dosing and timing. By leveraging a low intensity electric field to modify the concentration driven diffusion across a nanofluidic membrane, the rate of drug administration can be increased, decreased or stopped via Bluetooth remote command. We demonstrate in vitro the release modulation of enalapril and methotrexate, first-line therapeutics for treatment of hypertension and rheumatoid arthritis, respectively. Further, we show reliable remote communication and device biocompatibility via in vivo studies. Unlike a pulsatile release regimen typical of some conventional controlled delivery systems, our implant offers a continuous drug administration that avoids abrupt fluctuations, which could affect response and tolerability. Our system could set the foundation for an on-demand delivery platform technology for long term management of chronic diseases.

Graphical abstract: Remotely controlled nanofluidic implantable platform for tunable drug delivery

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Article information

23 Apr 2019
31 May 2019
First published
03 Jun 2019

Lab Chip, 2019,19, 2192-2204
Article type

Remotely controlled nanofluidic implantable platform for tunable drug delivery

N. Di Trani, A. Silvestri, G. Bruno, T. Geninatti, C. Y. X. Chua, A. Gilbert, G. Rizzo, C. S. Filgueira, D. Demarchi and A. Grattoni, Lab Chip, 2019, 19, 2192
DOI: 10.1039/C9LC00394K

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