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 |
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| Format: | Journal Article |
| Sprache: | Englisch |
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02.06.2021
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| ISSN: | 1948-7193, 1948-7193 |
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| Abstract | 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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| AbstractList | 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. 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.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. |
| Author | Laux, Peter Yang, Yin Dakua, Sarada Prasad Singh, Ajay Vikram Al Ansari, Abdulla Balakrishnan, Shidin Mathews, Divya Elsa Chandrasekar, Vaisali Janapareddy, Poonam Luch, Andreas Garcia-Canibano, Beatriz Abinahed, Julien |
| Author_xml | – sequence: 1 givenname: Ajay Vikram orcidid: 0000-0002-9875-7727 surname: Singh fullname: Singh, Ajay Vikram organization: Department of Chemical and Product Safety, German Federal Institute for Risk Assessment (BfR), Max-Dohrn-Straße 8-10, 10589 Berlin, Germany – sequence: 2 givenname: Vaisali surname: Chandrasekar fullname: Chandrasekar, Vaisali organization: Department of Surgery, Hamad Medical Corporation (HMC), 3050 Doha, Qatar – sequence: 3 givenname: Poonam surname: Janapareddy fullname: Janapareddy, Poonam organization: Department of Surgery, Hamad Medical Corporation (HMC), 3050 Doha, Qatar – sequence: 4 givenname: Divya Elsa surname: Mathews fullname: Mathews, Divya Elsa organization: Department of Surgery, Hamad Medical Corporation (HMC), 3050 Doha, Qatar – sequence: 5 givenname: Peter orcidid: 0000-0002-0351-3392 surname: Laux fullname: Laux, Peter organization: Department of Chemical and Product Safety, German Federal Institute for Risk Assessment (BfR), Max-Dohrn-Straße 8-10, 10589 Berlin, Germany – sequence: 6 givenname: Andreas surname: Luch fullname: Luch, Andreas organization: Department of Chemical and Product Safety, German Federal Institute for Risk Assessment (BfR), Max-Dohrn-Straße 8-10, 10589 Berlin, Germany – sequence: 7 givenname: Yin surname: Yang fullname: Yang, Yin organization: College of Science and Engineering, Hamad Bin Khalifa University (HBKU), 24404 Doha, Qatar – sequence: 8 givenname: Beatriz surname: Garcia-Canibano fullname: Garcia-Canibano, Beatriz organization: Department of Surgery, Hamad Medical Corporation (HMC), 3050 Doha, Qatar – sequence: 9 givenname: Shidin surname: Balakrishnan fullname: Balakrishnan, Shidin organization: Department of Surgery, Hamad Medical Corporation (HMC), 3050 Doha, Qatar – sequence: 10 givenname: Julien surname: Abinahed fullname: Abinahed, Julien organization: Department of Surgery, Hamad Medical Corporation (HMC), 3050 Doha, Qatar – sequence: 11 givenname: Abdulla surname: Al Ansari fullname: Al Ansari, Abdulla organization: Department of Surgery, Hamad Medical Corporation (HMC), 3050 Doha, Qatar – sequence: 12 givenname: Sarada Prasad surname: Dakua fullname: Dakua, Sarada Prasad organization: Department of Surgery, Hamad Medical Corporation (HMC), 3050 Doha, Qatar |
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