An International Nanotechnology Collaboration is the Monthly Publication Highlight
October 28, 2015
An international interdisciplinary research project that uses nanotechnology to help predict anticancer drug release has been named the October 2015 UK College of Pharmacy Publication Highlight.
The paper was published in Journal of Controlled Release and was entitled “Mechanistic model and analysis of doxorubicin release from liposomal formulations.”
This research was a collaborative effort between investigators in the College’s Department of Pharmaceutical Sciences, including Kyle Fugit, lead author on the paper and currently a Development Scientist at Metrics Contract Services, Tian-Xiang Xiang, Staff Scientist, Sogol Kangarlou, Postdoctoral Fellow, Paul Bummer, Associate Professor, and Bradley Anderson, Professor. In addition, Du Hyung Choi, Assistant Professor at the University of South Korea, and Eva Csuhai, Professor at Transylvania University, participated in this project.
Nanoparticles have been explored for targeting tumors and reducing anticancer drug toxicity to healthy tissue in cancer patients, but their success has been limited by several factors. One of these factors is the inability to predict drug release from nanoparticle delivery systems. Predicting drug release from nanoparticles requires reliable mathematical models that are able to describe the mechanism and provide predictions of drug release and potential efficacy in patients. A comprehensive understanding of the mechanism of drug release would allow investigators to design, develop and optimize new, more effective nanoparticle drug delivery systems. This publication demonstrates the successful development and application of a mechanistic mathematical model that is able to predict release of the anticancer agent doxorubicin from a nanoparticle drug delivery system resembling the FDA-approved DOXIL®, one of the most important liposomal products. The model described in the highlighted publication incorporates the chemical properties of doxorubicin, the liposome nanoparticle, and various properties of the excipients employed in the delivery system. The model was validated in that it predicted drug release under various environmental conditions which were evaluated experimentally. Importantly, the model predictions extended to release beyond the conditions that were evaluated experimentally. This work demonstrates for the first time a comprehensive mechanistic model capable of predicting drug release from liposome nanoparticles and an approach that may be useful for the development of models to predict drug release in other nanoparticle drug delivery systems.
“The importance of nanoparticle drug delivery systems emanates from their significant advantages as delivery systems, including delivering poorly soluble drug candidates to the target, prolonging systemic circulation, reducing toxicity, and controlling the kinetics of drug release. Predictive mathematical models that relate drug structure and formulation to drug release rate as described in this highlighted publication will serve to greatly augment the efficacy and successful clinical implementation of these therapeutics, “said Linda Dwoskin, Associate Dean for Research.