Computationally Guided Intracerebral Drug Delivery via Chronically Implanted Microdevices

• Main Authors: Ramadi, Khalil (Author), Bashyam, Ashvin (Author), Frangieh, Chris J. (Author), Rousseau, Erin Byrne (Author), Cotler, Max Joseph (Author), Langer, Robert S (Author), Graybiel, Ann M (Author), Cima, Michael J. (Author)
• Other Authors: Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor), McGovern Institute for Brain Research at MIT (Contributor), Massachusetts Institute of Technology. Department of Materials Science and Engineering (Contributor), Massachusetts Institute of Technology. Department of Mechanical Engineering (Contributor), Koch Institute for Integrative Cancer Research at MIT (Contributor)
• Format: Article
• Language: English
• Published: Elsevier BV, 2020-09-09T13:37:35Z.
• Subjects: Article
• Online Access: Get fulltext

 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.