Predicting the tissue depth for remote triggering of drug delivery systems.
Predicting the tissue depth for remote triggering of drug delivery systems.
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DOI:
10.1016/j.jconrel.2018.07.033
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发表时间:
2018-09-28
期刊:
影响因子:
--
通讯作者:
Kohane DS
中科院分区:
文献类型:
--
作者:
Rwei AY;Wang B;Ji T;Kohane DS
Externally triggerable drug delivery systems have promising potential in providing flexible control of the timing, duration, and intensity of treatment according to patient’s needs, while reducing side effects and increasing therapeutic efficacy. However, a limitation to translating such systems into clinical practice is the difficulty to predict the tissue depth at which such systems could be safely used in vivo (e.g. activatable at the target site with a clinically-safe energy dosage). An effective method is needed to evaluate the clinical potential of externally triggerable drug delivery systems. Here we have a method and approach to predicting the tissue depth at which a drug delivery system can be safely triggered in vivo by an external energy source. We used in vitro and ex vivo experiments combined with a mathematical model to develop a method to predict activated drug release at different tissue depths, which was then validated in vivo. We constructed these models for liposomal drug delivery systems triggered by two of the most commonly studied external stimuli: ultrasound and near infrared light. We developed the approach in two prevalent tissue types: muscle and fat. Our method identified two important parameters in the activation of drug delivery systems in tissue: 1) the ability of the activation energy to penetrate tissue, 2) the sensitivity of the system to the activation source. The method was validated by correlation with triggered sciatic nerve block in the rat in vivo, demonstrating that this approach provided an accurate estimate of activated release at different tissue depths.
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影响因子:
28.1
作者:
Rwei AY;Paris JL;Wang B;Wang W;Axon CD;Vallet-Regí M;Langer R;Kohane DS
通讯作者:
Kohane DS
影响因子:
15
作者:
Huschka, Ryan;Zuloaga, Jorge;Knight, Mark W.;Brown, Lisa V.;Nordlander, Peter;Halas, Naomi J.
通讯作者:
Halas, Naomi J.
影响因子:
3.4
作者:
Olbrich, K;Rawicz, W;Evans, E
通讯作者:
Evans, E
影响因子:
2.2
作者:
DerSimonian, Rebecca;Kacker, Raghu
通讯作者:
Kacker, Raghu
影响因子:
16.6
作者:
Carter, Kevin A.;Shao, Shuai;Hoopes, Matthew I.;Luo, Dandan;Ahsan, Bilal;Grigoryants, Vladimir M.;Song, Wentao;Huang, Haoyuan;Zhang, Guojian;Pandey, Ravindra K.;Geng, Jumin;Pfeifer, Blaine A.;Scholes, Charles P.;Ortega, Joaquin;Karttunen, Mikko;Lovell, Jonathan F.
通讯作者:
Lovell, Jonathan F.