External manipulation of nanostructure in photoresponsive lipid depot matrix to control and predict drug release in vivo

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• 作者：Wye-Khay Fong^a ; ^b ; Tracey L. Hanley^c ; Benjamin Thierry^d ; Adrian Hawley^e ; Ben J. Boyd^a ; ^f ; ^{ben.boyd@monash.edu" class="auth_mail" title="E-mail the corresponding author} ; Cornelia B. Landersdorfer^a ; ^g ; ^{cornelia.landersdorfer@monash.edu" class="auth_mail" title="E-mail the corresponding author}
• 关键词：Photothermal activation ; Lipid ; Liquid crystalline mesophase ; Triggerable drug delivery ; Cubic phase ; Pharmacokinetic modeling
• 刊名：Journal of Controlled Release
• 出版年：2016
• 出版时间：28 April 2016
• 年：2016
• 卷：228
• 期：Complete
• 页码：67-73
• 全文大小：598 K

文摘

On-demand drug delivery systems are highly promising to control the time-course of drug release and ultimately optimize drug concentration time profiles in patients. Lipid based lyotropic liquid crystalline mesophases have demonstrated exceptional responsiveness to external stimuli such as heat, pH and light. Our objective was to quantitatively characterize the time-course of light activated drug release from near infrared (NIR) activated photothermal systems using ex vivo and in vivo studies. Photoresponsive hybrid gold nanorod-liquid crystalline matrices were prepared and loaded into custom-made implants which were inserted into subcutaneous tissues in rats. Time resolved SAXS studies showed the abdomen to be the best site of implantation to achieve in vivo activation of the subcutaneous dose from by the NIR laser. External control of drug release was achieved via NIR laser light and plasma concentrations of the model drug were determined over time. Laser activation achieved a phase change of the photoresponsive formulations and thereby a considerable change in the rate of drug release. Population pharmacokinetic modeling of all results simultaneously revealed a two stage release process unique to these liquid crystalline matrices. The developed structural model was able to successfully describe also the results of our previous study in 2009 where a change in temperature was utilized to trigger subcutaneous drug release. Thus, modeling of the data proved to be a valuable analytical tool which provided a quantitative understanding of the time-course of drug release in vivo and will be essential in the development of these matrices as on-demand release systems.