4.8 Article

Meta-Analysis of Nanoparticle Delivery to Tumors Using a Physiologically Based Pharmacokinetic Modeling and Simulation Approach

期刊

ACS NANO
卷 14, 期 3, 页码 3075-3095

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acsnano.9b08142

关键词

advanced material; drug delivery; nanomedicine; nanoparticle; physiologically based pharmacokinetic modeling; tissue biothstribution; tumor delivery

资金

  1. National Institute of Biomedical Imaging and Bioengineering, US National Institutes of Health (NIH) [R03EB025566, R03EB026045]
  2. New Faculty Start-up funds of Kansas State University
  3. SUCCESS-FYI - College of Veterinary Medicine at Kansas State University

向作者/读者索取更多资源

Numerous studies have engineered nanoparticles with different physicochemical properties to enhance the delivery efficiency to solid tumors, yet the mean and median delivery efficiencies are only 1.48% and 0.70% of the injected dose (%ID), respectively, according to a study using a nonphysiologically based modeling approach based on published data from 2005 to 2015. In this study, we used physiologically based pharmacokinetic (PBPK) models to analyze 376 data sets covering a wide range of nanomedicines published from 2005 to 2018 and found mean and median delivery efficiencies at the last sampling time point of 2.23% and 0.76%ID, respectively. Also, the mean and median delivery efficiencies were 2.24% and 0.76%ID at 24 h and were decreased to 1.23% and 0.35%ID at 168 h, respectively, after intravenous administration. While these delivery efficiencies appear to be higher than previous findings, they are still quite low and represent a critical barrier in the clinical translation of nanomedicines. We explored the potential causes of this poor delivery efficiency using the more mechanistic PBPK perspective applied to a subset of gold nanoparticles and found that low delivery efficiency was associated with low distribution and permeability coefficients at the tumor site (P < 0.01). We also demonstrate how PBPK modeling and simulation can be used as an effective tool to investigate tumor delivery efficiency of nanomedicines.

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