(176av) Understanding Nanoparticle Distribution within the Peritoneal Cavity for the Treatment of Ovarian Cancer Metastasis

Authors: 
Hargrove, D., University of Connecticut
Ahsan, S., University of Connecticut
Chaudhuri, B., University of Connecticut
Lu, X., University of Connecticut
Salner, A., Hartford Hospital
The peritoneal cavity is common site of metastatic disease from a variety of cancers including ovarian, digestive tract, lung and breast; it is also the site for a wide spectrum of non-neoplastic conditions. Therapeutic agents have been administered intraperitoneally (i.p.) in order to increase local drug concentrations. Nanoparticle-based therapeutics have become increasingly popular for i.p. delivery due to their increased peritoneal residence time and the ability of the particles to freely move throughout the entire cavity for uniform distribution of various therapeutics. It is, however, unknown what specific nanoparticle formulation and infusion characteristics optimally distribute these particles throughout the cavity to uniformly treat all tumor tissues.

The main objective of this work was to advance the fundamental understanding of the mechanics of complex multiphase flow patterns, distribution and deposition of nanoparticles within the peritoneal cavity by creating a discrete phase model using an Euler-Lagrangian approach. A computer simulation was created to help predict optimal nanoparticle formulation characteristics to maximize nanoparticle distribution throughout the peritoneal cavity and also to maximize tumor uptake of the particles. The fluid phase was treated as a continuum and governed by the Navier-Stokes equations, while the dispersed phase was solved by tracking a large number of particles through the calculated flow field. An optimized dynamic meshing model was employed using the Fluent CFD package to create the computational grid in the dynamic domain of the peritoneal cavity. After running various simulations, the mass, suspension viscosity, fluid volume, infusion rate and infusion port placement was optimized in order to promote the most comprehensive coverage of the particles in the peritoneal cavity. These results were then corroborated with real-time in vivo, 3D fluorescence imaging of mesoporous silica nanoparticles within the peritoneal cavity of mice bearing peritoneal metastasis at various time points up to 24 hours post injection. It was found that irrespective of the location of the metastasized tumors, the nanoparticles were able to selectively accumulate on the tumor tissues using the guiding formulation parameters determined in the simplified computer model.

The results of this study were used to gain insight in the overall design on nanoparticle formulations for the treatment of peritoneal metastasis by determining formulation specific characteristics that can be manipulated to promote total peritoneal cavity coverage and tumor accumulation, understand injection port placement and understand the optimal nanoparticle infusion rate.