Drug transport kinetics of intravascular triggered drug delivery systems

Timo L.M. ten Hagen, Matthew R. Dreher, Sara Zalba, Ann L.B. Seynhaeve, Mohamadreza Amin, Li Li, Dieter Haemmerich*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

27 Citations (Scopus)

Abstract

Intravascular triggered drug delivery systems (IV-DDS) for local drug delivery include various stimuli-responsive nanoparticles that release the associated agent in response to internal (e.g., pH, enzymes) or external stimuli (e.g., temperature, light, ultrasound, electromagnetic fields, X-rays). We developed a computational model to simulate IV-DDS drug delivery, for which we quantified all model parameters in vivo in rodent tumors. The model was validated via quantitative intravital microscopy studies with unencapsulated fluorescent dye, and with two formulations of temperature-sensitive liposomes (slow, and fast release) encapsulating a fluorescent dye as example IV-DDS. Tumor intra- and extravascular dye concentration dynamics were extracted from the intravital microscopy data by quantitative image processing, and were compared to computer model results. Via this computer model we explain IV-DDS delivery kinetics and identify parameters of IV-DDS, of drug, and of target tissue for optimal delivery. Two parameter ratios were identified that exclusively dictate how much drug can be delivered with IV-DDS, indicating the importance of IV-DDS with fast drug release (~sec) and choice of a drug with rapid tissue uptake (i.e., high first-pass extraction fraction). The computational model thus enables engineering of improved future IV-DDS based on tissue parameters that can be quantified by imaging.

Original languageEnglish
Article number920
JournalCommunications Biology
Volume4
Issue number1
DOIs
Publication statusPublished - 28 Jul 2021

Bibliographical note

Funding Information:
We thank the National Institutes of Health Medical Arts team for creating Fig. 1 and Fig. S9. We thank O. Friman, M. Schwenke, and T. Preusser from the Fraunhofer MeVis Institute for Medical Image Computing for assistance with image-processing and motion compensation methods. Supported by NIH grant R01CA181664 (D.H.) and NIH C06 RR018823 from the Extramural Research Facilities Program of the National Center for Research Resources (MUSC).

Publisher Copyright:
© 2021, The Author(s).

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