Doctoral Dissertation Defense – Michael Donzanti

BME PhD Candidate Michael Donzanti will be defending their dissertation:


A Multi-Faceted Approach for Addressing Poor Drug Transport Into the Lymph Node


  • Location: Fintech Building
  • Zoom Link:
  • Date: Thursday, January 11th, 2024
  • Time: 1 pm
  • Committee: Jason P. Gleghorn, Ryan Zurakowski, John H. Slater, Catherine A. Fromen


Poor drug penetration into the lymph node lobule has been observed in numerous studies and is of great significance during the treatment of lymph node resident diseases, such as HIV and metastatic cancer. In HIV, the lymph nodes act as a long-lasting viral reservoir for patients receiving standard care therapy. While treatment methods have improved in recent decades, no sterilizing cure has been developed due to this pharmacological sanctuary site. In many metastatic cancers, the lymph node is the first site of tumor spread. While much of the pathology is left to be uncovered, lymph node metastases severely harm prognosis and aid in disease progression, with current therapeutic strategies often left ineffective. Our lack of insight on the transport phenomena occurring at these specialized boundaries limits our options. This dissertation develops tools and approaches to develop a mechanistic understanding of drug transport in the lymph node and leverages these findings to advance therapeutic drug delivery to the lymph node.

Heterogenous distribution of small molecules within the lymph node lobule underpins, in part, our current lack of therapeutic efficiency. This is driven by the lack of connections made between variability in lymph node geometry, drug biochemical properties, and mechanisms of transport. The ability to accurately produce 3-dimensional anatomical reconstructions of the lymph node can aid quantitative morphological analysis, mapping of spatial drug distribution, and understanding drug specific variations to transport. Therefore, we developed a novel tissue reconstruction pipeline to produce anatomically accurate 3D geometries of murine lymph nodes. Using custom tissue sectioning methods, staining and imaging devices, and automated alignment and segmentation algorithms, relevant tissue compartments were easily segmented and reconstructed into 3D volumes. Using these 3D objects, spatial drug transport mechanisms and drug distributions could be modeled and predicted.

Next, we investigated how cell-mediated transport mechanisms contributed to overall antiretroviral (ARV) concentrations within the lymph node. Using evidence from spatial mass spectrometry modeling and uptake of ARV species by leukocytes, we hypothesized that for non-lipophilic species cell-mediated transport was a dominant mechanism. We developed a functional antibody blocking strategy to block lymphocyte ingress to test this mechanism. While some ARV species exhibited trends of cell-mediated transport, the contribution of this mechanism was smaller than originally predicted. From these findings, we also compared different drug classes and determined certain ARVs displayed stronger lymph node accumulation than other species. These findings can be used to inform the design of ARV species to target the lymph node HIV reservoir.

Lastly, leveraging mechanisms of lymphocyte ingress into the lymph node for therapeutic design, we developed a delivery strategy utilizing a cell mimetic delivery vehicle. These drug carriers have the ability to home to the lymph node and transport across the high endothelial venules into the lobule to locally release small molecule therapeutics. We validated targeting and safety in vivo and confirmed strong lobule uptake with minimal immune responses. We next showed loading and release of a small molecule chemotherapeutic, cisplatin, which retained cytotoxic effect after release. Finally, using mass spectrometry techniques, we confirmed administration of cisplatin loaded drug carriers resulted in increased lymph node concentrations as compared to free drug. We believe this system serves as a backbone technology for many possible drug delivery applications.