title: Computational Modeling of Tumor Response to Drug Release from Vasculature-Bound Nanoparticles.
abstract: Systemically injected nanoparticle (NPs) targeting tumor vasculature offer a venue for anti-angiogenic therapies as well as cancer detection and imaging. Clinical application has been limited, however, due to the challenge of elucidating the complex interplay of nanotechnology, drug, and tumor parameters. A critical factor representing the likelihood of endothelial adhesion is the NP vascular affinity, a function of vascular receptor expression and NP size and surface-bound ligand density. We propose a theoretical framework to simulate the tumor response to vasculature-bound drug-loaded NPs and examine the interplay between NP distribution and accumulation as a function of NP vascular affinity, size, and drug loading and release characteristics. The results show that uniform spatial distribution coupled with high vascular affinity is achievable for smaller NPs but not for larger sizes. Consequently, small (100 nm) NPs with high vascular affinity are predicted to be more effective than larger (1000 nm) NPs with similar affinity, even though small NPs have lower drug loading and local drug release compared to the larger NPs. Medium vascular affinity coupled with medium or larger sized NPs is also effective due to a more uniform distribution with higher drug loading and release. Low vascular affinity hampered treatment efficacy regardless of NP size, with larger NPs additionally impeded by heterogeneous distribution and drug release. The results further show that increased drug diffusivity mainly benefits heterogeneously distributed NPs, and would negatively affect efficacy otherwise due to increased wash-out. This model system enables evaluation of efficacy for vascular-targeted drug-loaded NPs as a function of critical NP, drug, and tumor parameters.
authors.affiliation: Department of Bioengineering, University of Louisville, Louisville, Kentucky, United States of America.
authors.forename: Louis T
authors.initials: LT
authors.lastname: Curtis
authors.affiliation: Department of Engineering Sciences and Applied Mathematics, Northwestern University, Chicago, Illinois, United States of America.
authors.forename: Min
authors.initials: M
authors.lastname: Wu
authors.affiliation: Department of Mathematics, University of California, Irvine, California, United States of America.|Department of Biomedical Engineering, University of California, Irvine, California, United States of America.|Chao Family Comprehensive Cancer Center, University of California, Irvine, California, United States of America.
authors.forename: John
authors.initials: J
authors.lastname: Lowengrub
authors.affiliation: Department of Translational Imaging and Department of Nanomedicine, Houston Methodist Research Institute, Houston, Texas, United States of America.
authors.forename: Paolo
authors.initials: P
authors.lastname: Decuzzi
authors.affiliation: Department of Bioengineering, University of Louisville, Louisville, Kentucky, United States of America.|James Graham Brown Cancer Center, University of Louisville, Louisville, Kentucky, United States of America.
authors.forename: Hermann B
authors.initials: HB
authors.lastname: Frieboes
mesh_terms: D000970:Antineoplastic Agents / Q000008:administration & dosage / Q000737:chemistry; D004337:Drug Carriers / Q000737:chemistry*; D065546:Drug Liberation; D006801:Humans; D008962:Models, Theoretical; D053758:Nanoparticles / Q000737:chemistry*; D009369:Neoplasms / Q000098:blood supply / Q000188:drug therapy / Q000473:pathology; D009389:Neovascularization, Pathologic; D010100:Oxygen / Q000378:metabolism; D010316:Particle Size
chemical_list: D000970:Antineoplastic Agents; D004337:Drug Carriers; D010100:Oxygen