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Updated: Sep 13, 2025
08:22
CRISPR/Cas9-mediated Targeted Integration In Vivo Using a Homology-mediated End Joining-based Strategy
Published on: March 12, 2018
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Revolutionizing CRISPR technology with artificial intelligence
Min-Gyeong Kim1,2, Min-Ji Go1,2, Seung-Hun Kang3
1Biomedical Research Division, Korea Institute of Science and Technology, Seoul, Republic of Korea.
Experimental & Molecular Medicine
|July 31, 2025
Summary
Artificial intelligence (AI) is revolutionizing genome engineering by enhancing CRISPR technology. AI improves guide RNA design, predicts off-target effects, and aids in discovering novel CRISPR systems for safer, more precise gene therapies.
Area of Science:
- Genetics and Genomics
- Biotechnology
- Bioinformatics
Background:
- Genome engineering has advanced significantly, with CRISPR-Cas systems offering unprecedented precision in targeting specific DNA regions.
- Current CRISPR tools, including nucleases, base editors, and prime editors, enable diverse genetic modifications but face challenges like variable editing outcomes and off-target effects.
Purpose of the Study:
- To explore the transformative role of Artificial Intelligence (AI) in advancing CRISPR genome engineering technology.
- To highlight how AI integration addresses existing limitations and enhances the capabilities of CRISPR-based tools.
Main Methods:
- Leveraging large-scale experimental datasets to train AI algorithms for predicting CRISPR activity and designing guide RNAs.
- Utilizing AI for the identification and design of novel CRISPR systems and Cas proteins.
- Applying AI to refine existing CRISPR editing modalities: nucleases, base editors, and prime editors.
Main Results:
- AI significantly enhances guide RNA design, leading to improved targeting specificity and efficiency.
- AI-based prediction models effectively identify and mitigate unintended off-target mutations.
- AI facilitates the discovery of new CRISPR systems, expanding the scope of genome engineering.
Conclusions:
- AI integration is crucial for overcoming current challenges in CRISPR technology, such as off-target effects and variable editing efficiency.
- AI-driven advancements in CRISPR tools pave the way for more precise, efficient, and safer gene therapies.
- The synergy between AI and CRISPR promises to accelerate innovation in personalized medicine and next-generation gene editing applications.
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