Drug Retention and Tumor Distribution of Polymeric Micelles for Cancer Therapy

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 therapeutics.