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Could Artificial Intelligence Revolutionize the Development of Nanovectors for Gene Therapy and Mrna Vaccines? Publisher



Hasanzadeh A1, 2 ; Hamblin MR3, 4 ; Kiani J5, 6 ; Noori H1, 2 ; Hardie JM9 ; Karimi M1, 2, 5, 7, 8 ; Shafiee H9
Authors
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Authors Affiliations
  1. 1. Cellular and Molecular Research Center, Iran University of Medical Sciences, Tehran, 1449614535, Iran
  2. 2. Department of Medical Nanotechnology, Faculty of Advanced Technologies in Medicine, Iran University of Medical Sciences, Tehran, 1449614535, Iran
  3. 3. Laser Research Centre, Faculty of Health Science, University of Johannesburg, Doornfontein, 2028, South Africa
  4. 4. Radiation Biology Research Center, Iran University of Medical Sciences, Tehran, Iran
  5. 5. Oncopathology Research Center, Iran University of Medical Sciences, Tehran, 1449614535, Iran
  6. 6. Department of Molecular Medicine, Faculty of Advanced Technologies in Medicine, Iran University of Medical Sciences, Tehran, Iran
  7. 7. Research Center for Science and Technology in Medicine, Tehran University of Medical Sciences, Tehran, 141556559, Iran
  8. 8. Applied Biotechnology Research Centre, Tehran Medical Science, Islamic Azad University, Tehran, 1584743311, Iran
  9. 9. Division of Engineering in Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, 02139, MA, United States

Source: Nano Today Published:2022


Abstract

Gene therapy enables the introduction of nucleic acids like DNA and RNA into host cells, and is expected to revolutionize the treatment of a wide range of diseases. This growth has been further accelerated by the discovery of CRISPR/Cas technology, which allows accurate genomic editing in a broad range of cells and organisms in vitro and in vivo. Despite many advances in gene delivery and the development of various viral and non-viral gene delivery vectors, the lack of highly efficient non-viral systems with low cellular toxicity remains a challenge. The application of cutting-edge technologies such as artificial intelligence (AI) has great potential to find new paradigms to solve this issue. Herein, we review AI and its major subfields including machine learning (ML), neural networks (NNs), expert systems, deep learning (DL), computer vision and robotics. We discuss the potential of AI-based models and algorithms in the design of targeted gene delivery vehicles capable of crossing extracellular and intracellular barriers by viral mimicry strategies. We finally discuss the role of AI in improving the function of CRISPR/Cas systems, developing novel nanobots, and mRNA vaccine carriers. © 2022 Elsevier Ltd
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