Emerging Application of Nanorobotics and Artificial Intelligence To Cross the BBB: Advances in Design, Controlled Maneuvering, and Targeting of the Barriers

The blood-brain barrier (BBB) is a prime focus for clinicians to maintain the homeostatic function in health and deliver the theranostics in brain cancer and number of neurological diseases. The structural hierarchy and in situ biochemical signaling of BBB neurovascular unit have been primary target...

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Veröffentlicht in:ACS chemical neuroscience Jg. 12; H. 11; S. 1835
Hauptverfasser: Singh, Ajay Vikram, Chandrasekar, Vaisali, Janapareddy, Poonam, Mathews, Divya Elsa, Laux, Peter, Luch, Andreas, Yang, Yin, Garcia-Canibano, Beatriz, Balakrishnan, Shidin, Abinahed, Julien, Al Ansari, Abdulla, Dakua, Sarada Prasad
Format: Journal Article
Sprache:Englisch
Veröffentlicht: United States 02.06.2021
Schlagworte:
nanorobots
machine learning and artificial intelligence
nanoparticles
Blood−brain barrier
transcytosis
bioengineering
ISSN:1948-7193, 1948-7193
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Zusammenfassung:The blood-brain barrier (BBB) is a prime focus for clinicians to maintain the homeostatic function in health and deliver the theranostics in brain cancer and number of neurological diseases. The structural hierarchy and in situ biochemical signaling of BBB neurovascular unit have been primary targets to recapitulate into the in vitro modules. The microengineered perfusion systems and development in 3D cellular and organoid culture have given a major thrust to BBB research for neuropharmacology. In this review, we focus on revisiting the nanoparticles based bimolecular engineering to enable them to maneuver, control, target, and deliver the theranostic payloads across cellular BBB as nanorobots or nanobots. Subsequently we provide a brief outline of specific case studies addressing the payload delivery in brain tumor and neurological disorders (e.g., Alzheimer's disease, Parkinson's disease, multiple sclerosis, etc.). In addition, we also address the opportunities and challenges across the nanorobots' development and design. Finally, we address how computationally powered machine learning (ML) tools and artificial intelligence (AI) can be partnered with robotics to predict and design the next generation nanorobots to interact and deliver across the BBB without causing damage, toxicity, or malfunctions. The content of this review could be references to multidisciplinary science to clinicians, roboticists, chemists, and bioengineers involved in cutting-edge pharmaceutical design and BBB research.
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ISSN:1948-7193
1948-7193
DOI:10.1021/acschemneuro.1c00087