Computationally Guided Intracerebral Drug Delivery via Chronically Implanted Microdevices
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1-s2.0-S2211124720307142-main.pdf
Description
Published version
Size
2.59 MB
Format
Adobe PDF
Checksum (MD5)
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Author(s)
Ramadi, Khalil
Bashyam, Ashvin
Frangieh, Chris J.
Rousseau, Erin Byrne
Cotler, Max Joseph
Langer, Robert S
Graybiel, Ann M
Cima, Michael J.
Date Issued
June 2020
Journal
Cell Reports
Publisher
Elsevier BV
Citation
Ramadi, Khalil B. et al. “Computationally Guided Intracerebral Drug Delivery via Chronically Implanted Microdevices.” Cell Reports, 31, 10 (June 2020): 107734 © 2020 The Author(s)
Version
Final published version
Abstract
Treatments for neurologic diseases are often limited in efficacy due to poor spatial and temporal control over their delivery. Intracerebral delivery partially overcomes this by directly infusing therapeutics to the brain. Brain structures, however, are nonuniform and irregularly shaped, precluding complete target coverage by a single bolus without significant off-target effects and possible toxicity. Nearly complete coverage is crucial for effective modulation of these structures. We present a framework with computational mapping algorithms for neural drug delivery (COMMAND) to guide multi-bolus targeting of brain structures that maximizes coverage and minimizes off-target leakage. Custom-fabricated chronic neural implants leverage rational fluidic design to achieve multi-bolus delivery in rodents through a single infusion of radioactive tracer (Cu-64). The resulting spatial distributions replicate computed spatial coverage with 5% error in vivo, as detected by positron emission tomography. COMMAND potentially enables accurate, efficacious targeting of discrete brain regions.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
McGovern Institute for Brain Research at MIT
Massachusetts Institute of Technology. Department of Materials Science and Engineering
Massachusetts Institute of Technology. Department of Mechanical Engineering
Koch Institute for Integrative Cancer Research at MIT
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivs License
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DOI of Published Version
https://doi.org/10.1016/j.celrep.2020.107734
