Comparison of the uptake of methacrylate-based nanoparticles in static and dynamic in vitro systems as well as in vivo.

Polymer-based nanoparticles are promising drug delivery systems allowing the development of new drug and treatment strategies with reduced side effects. However, it remains a challenge to screen for new and effective nanoparticle-based systems in vitro. Important factors influencing the behavior of nanoparticles in vivo cannot be simulated in screening assays in vitro, which still represent the main tools in academic research and pharmaceutical industry. These systems have serious drawbacks in the development of nanoparticle-based drug delivery systems, since they do not consider the highly complex processes influencing nanoparticle clearance, distribution, and uptake in vivo. In particular, the transfer of in vitro nanoparticle performance to in vivo models often fails, demonstrating the urgent need for novel in vitro tools that can imitate aspects of the in vivo situation more accurate. Dynamic cell culture, where cells are cultured and incubated in the presence of shear stress has the potential to bridge this gap by mimicking key-features of organs and vessels. Our approach implements and compares a chip-based dynamic cell culture model to the common static cell culture and mouse model to assess its capability to predict the in vivo success more accurately, by using a well-defined poly((methyl methacrylate)-co-(methacrylic acid)) and poly((methyl methacrylate)-co-(2-dimethylamino ethylmethacrylate)) based nanoparticle library. After characterization in static and dynamic in vitro cell culture we were able to show that physiological conditions such as cell-cell communication of co-cultured endothelial cells and macrophages as well as mechanotransductive signaling through shear stress significantly alter cellular nanoparticle uptake. In addition, it could be demonstrated by using dynamic cell cultures that the in vivo situation is simulated more accurately and thereby can be applied as a novel system to investigate the performance of nanoparticle systems in vivo more reliable.