Artificial Intelligence-Based Approaches for AAV Vector Engineering.

Journal: Advanced science (Weinheim, Baden-Wurttemberg, Germany)
PMID: 39932449

Abstract

Adeno-associated virus (AAV) has emerged as a leading vector for gene therapy due to its broad host range, low pathogenicity, and ability to facilitate long-term gene expression. However, AAV vectors face limitations, including immunogenicity and insufficient targeting specificity. To enhance the efficacy of gene therapy, researchers have been modifying the AAV vector using various methods. Traditional experimental approaches for optimizing AAV vector are often time-consuming, resource-intensive, and difficult to replicate. The advancement of artificial intelligence (AI), particularly machine learning, offers significant potential to accelerate capsid optimization while reducing development time and manufacturing costs. This review compares traditional and AI-based methods of AAV vector engineering and highlights recent research in AAV engineering using AI algorithms.

Authors

  • Fangzhi Tan
    State Key Laboratory of Digital Medical Engineering, Department of Otolaryngology Head and Neck Surgery, Zhongda Hospital, School of Life Sciences and Technology, School of Medicine, Advanced Institute for Life and Health, Jiangsu Province High-Tech Key Laboratory for Bio-Medical Research, Southeast University, Nanjing, 210096, China.
  • Yue Dong
    Department of Anesthesiology, Mayo Clinic College of Medicine, Rochester, MN, United States.
  • Jieyu Qi
    Department of Neurology, Aerospace Center Hospital, School of Life Science, Beijing Institute of Technology, Beijing, 100081, China.
  • Wenwu Yu
    Department of Mathematics, Southeast University, Nanjing 210096, China; Faculty of Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia.
  • Renjie Chai
    State Key Laboratory of Digital Medical Engineering, Department of Otolaryngology Head and Neck Surgery, Zhongda Hospital, School of Life Sciences and Technology, School of Medicine, Advanced Institute for Life and Health, Jiangsu Province High-Tech Key Laboratory for Bio-Medical Research, Southeast University, Nanjing, 210096, China.

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