Abstract/Project Summary Polymeric micelles are powerful drug delivery vehicles with a promising future. There are currently no US Food and Drug Administration approved polymeric micelle formulations, but some have been approved by the European Medicines Agency and other international regulatory bodies. Traditional pharmacokinetic analysis focuses on two drug fractions-unbound free drug and drug which is bound to serum proteins. However, the inclusion of nanoparticles complicates pharmacokinetic analysis by introducing a third drug fraction which is nanomedicine encapsulated. Encapsulation into polymeric micelles alters drug partitioning to serum proteins. Polymeric micelles can preferentially accumulate into tumor tissues, improving tumor drug exposure. Little is known about how polymer-drug interactions influence drug partitioning between polymeric micelles and serum proteins. My preliminary data shows that we have developed an in vitro assay to measure micelle-protein partitioning which recapitulates known in vivo behavior, like the high protein binding of the drug warfarin. For the F99 phase of my proposal, I hypothesize that the in vitro partitioning of drug is related to polymer-drug interactions which we observe by NMR, micro-DSC, and molecular dynamics. In particular, we have shown that drug interaction with parts of the polymeric micelle hydrophilic corona leads to improved drug loading, and may lead to stronger retention in the polymeric micelles. In Aim 1.1, I propose to study how these measured polymer- drug interactions affect drug partitioning in a validated in vitro assay. This in vitro drug partitioning could correlate to tumor-drug exposure in vivo in a mouse model of triple negative breast cancer. In Aim 1.2, I hypothesize that improved micelle drug retention, as measured in vitro, will improve the distribution of drug to the tumor in vivo as measured by AUC and Cmax. Understanding how polymer-drug interactions influence partitioning and tumor exposure will lead to reduced preclinical studies and improved therapeutic outcomes. We will be able to select optimal formulations by applying in vitro partitioning results to pharmacokinetic modeling to predict tumor drug exposure. In Aim 1.3, we will analyze drug fractions in non-human primates to determine if drug partitioning is recapitulated in more human-like species. Altogether, the proposed F99 phase work will improve our understanding of polymeric micelle formulations and how drug retention affects tumor exposure and therapeutic efficacy. In the K00 phase, I propose to focus on polymer-nucleic acid and polymer-protein complexes for cancer therapeutics and vaccines. Utilizing the same principles from the F99 phase, polymer-cargo interactions can be used to inform targeted drug delivery of these different cargoes. My dissertation project and future postdoctoral work will provide the necessary training experience to prepare me for an independent research career focused on cancer the...