Nordlander, Peter2019-05-172020-05-012019-052019-04-19May 2019Nizzero, Sara. "A quantitative approach to discover predictors of biodistribution for drug delivery vectors in cancer.." (2019) Diss., Rice University. <a href="https://hdl.handle.net/1911/105955">https://hdl.handle.net/1911/105955</a>.https://hdl.handle.net/1911/105955Systemic aspects of cancer simultaneously offer the biggest clinical challenge and the most promising therapeutic niche in the treatment of solid tumors. In fact, treatment often fails in late stages due to the presence of metastasis, a migratory phenotype of cancer invasion. Metastases consist in cancer spread to distant organs which often presents characteristic high levels of heterogeneity and acquired resistance to treatments. Multi-stage injectable delivery vectors have proven powerful in exploiting systemic transport properties connected to physiological parameters to enhance tumor accumulation and directly improve therapeutic efficacy. The theoretical framework in which these concepts first developed is now known by the term transport oncophysics: the study of mass transport phenomena relevant to oncology with a physics-based approach. For injectable inorganic delivery vectors, the major innovation relies on the capability to tailor their organ distribution (biodistribution) upon injection. This capability comes from the controllable design of such systems, which present a discoidal shape with sizes in the micrometer range. While these systems have shown disruptive results in the treatment of triple negative breast cancer metastasis, there is still a lack of fundamental understanding on how patient-specific physiological parameters affect their biodistribution. However, it is well known that patient physiology is often dysregulated in cancer patients. These alterations can be caused by a multitude of reasons: cancer itself, the presence of concurring diseases or conditions, and previous treatment. This patient heterogeneity poses an additional challenge in therapeutic translation of injectable delivery systems. In this work, significant clinically relevant physiological parameters are screened, systematically altered, and quantitatively characterized as transport barriers for systemic delivery. Systematic in vivo biodistribution studies are conducted to address changes in biodistribution resulting from controlled alteration of specific physiological parameters. Uptake kinetic is characterized through time-resolved analysis, and investigated to inform on synergistic relationships among different parameters. A computational approach is then developed to identify a pharmacokinetic (PK) model able to predict the system behavior, and used to investigate the importance of several parameters, and functional relationships. This combined in vivo / in silico approach enables the quantitative description of mechanistic rules that determine the biodistribution of systemically injected delivery vectors. The framework that emerges from this study opens the way to a new paradigm for personalized adaptive therapy, where quantitative measurements, systematic analysis, and mathematical modeling can be combined to investigate and characterize functional relationships between quantitatively characterized physiological parameters and clinically relevant measurables for injectable inorganic delivery vectors.application/pdfengCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.Nanomedicinebiodistributiononcologydrug deliverymodelingpharmacokineticstransportphagocytic cellsmacrophagesneutrophilsplateletssilicon particlesThesis2019-05-17