TY - JOUR
T1 - Could artificial intelligence revolutionize the development of nanovectors for gene therapy and mRNA vaccines?
AU - Hasanzadeh, Akbar
AU - Hamblin, Michael R.
AU - Kiani, Jafar
AU - Noori, Hamid
AU - Hardie, Joseph M.
AU - Karimi, Mahdi
AU - Shafiee, Hadi
N1 - Publisher Copyright:
© 2022 Elsevier Ltd
PY - 2022/12
Y1 - 2022/12
N2 - 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.
AB - 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.
KW - AI
KW - CRISPR/Cas
KW - Gene delivery vehicles
KW - Gene therapy
KW - MRNA vaccine carriers
KW - Nanobots
UR - http://www.scopus.com/inward/record.url?scp=85141509642&partnerID=8YFLogxK
U2 - 10.1016/j.nantod.2022.101665
DO - 10.1016/j.nantod.2022.101665
M3 - Review article
AN - SCOPUS:85141509642
SN - 1748-0132
VL - 47
JO - Nano Today
JF - Nano Today
M1 - 101665
ER -