https://orcid.org/0000-0003-1113-6715
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Abstract
Purpose
This study investigated the brain targeting mechanism of doxorubicin-loaded polybutyl cyanoacrylate (PBCA) nanoparticles, particularly their interactions with the blood-brain barrier (BBB). The BBB protects the brain from drugs in the bloodstream and represents a crucial obstacle in the treatment of brain cancer.
Methods
An advanced computer model analyzed the brain delivery of two distinct formulations, Doxil® and surfactant-coated PBCA nanoparticles. Computational learning was combined with in vitro release and cell interaction studies to comprehend the underlying brain delivery pathways.
Results
Our analysis yielded a surprising discovery regarding the brain delivery mechanism of PBCA nanoparticles. While Doxil® exhibited the expected behavior, accumulating in the brain through extravasation in tumor tissue, PBCA nanoparticles employed a unique and previously uncharacterized mechanism. They underwent cell hitchhiking, resulting in a remarkable more than 1000-fold increase in brain permeation rate compared to Doxil® (2.59 × 10−4 vs 0.32 h−1).
Conclusion
The nonspecific binding to blood cells facilitated and intensified interactions of surfactant-coated PBCA nanoparticles with the vascular endothelium, leading to enhanced transcytosis. Consequently, the significant increase in circulation time in the bloodstream, coupled with improved receptor interactions, contributes to this remarkable uptake of doxorubicin into the brain.
Graphical Abstract
Declaration of Generative AI in Scientific Writing
During the preparation of this work, the authors used the AI tool ChatGPT v3.5 to improve the language and flow of speech. After using this tool/service, the authors reviewed and edited the content as needed and take full responsibility for the content of the publication.
Dedication
This work is dedicated to the cherished memory of Dr. David Begley, Senior Lecturer at King’s College London, whose profound impact on our understanding of brain delivery superhighways will forever be remembered.
Acknowledgment
The authors acknowledge Lixoft (Antony, France) for an academic license of Monolix Suite 2020R. M.G.W. acknowledges the National University of Singapore, Faculty of Science, and the Ministry of Education (Startup grant no. A-0004627-00-00 and Tier 1 grant no. A-0004337-00-00) for financial support. Cell studies were carried out within the state assignment of Ministry of Science and Higher Education of the Russian Federation (project FSSM-2022-0003). The graphical abstract was created with the AI tool ChatGPT v4 (DALL-E).
Author Contributions
All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.
Disclosure
The authors report no conflicts of interest in this work.