Evidence map›Paper›PMID 40745000›Full record

ReviewExperimental & molecular medicine2025

Revolutionizing CRISPR technology with artificial intelligence.

Min-Gyeong Kim, Min-Ji Go, Seung-Hun Kang, Soo-Hwan Jeong, Kayeong Lim

Abstract readReview
In one paragraph

Review in Experimental & molecular medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

29 citing papers in PubMed.

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  5. [Research Progress on the Application of CRISPR/Cas System in Rapid Testing of Drug-Resistant Bacteria in Clinical Practice].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2026
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  15. Nanocarrier-mediated CRISPR-Cas delivery: a novel approach against antibiotic-resistant superbugs.Saudi pharmaceutical journal : SPJ : the official publication of the Saudi Pharmaceutical Society · 2026
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  18. Protein engineering: status report.Protein engineering, design & selection : PEDS · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Min-Gyeong Kim *Biomedical Research Division, Korea Institute of Science and Technology, Seoul, Republic of Korea.
Min-Ji Go *Biomedical Research Division, Korea Institute of Science and Technology, Seoul, Republic of Korea.
Seung-Hun KangGraduate School of Biomedical Science and Engineering, Hanyang University, Seoul, Republic of Korea.
Soo-Hwan JeongBiomedical Research Division, Korea Institute of Science and Technology, Seoul, Republic of Korea.
Kayeong LimBiomedical Research Division, Korea Institute of Science and Technology, Seoul, Republic of Korea. kylim@kist.re.kr.ORCID http://orcid.org/0000-0002-6274-7252

Funding

Korea Institute of Science and Technology (KIST) 2V10573 and 2E33791National Research Foundation of Korea (NRF) RS-2023-00210965 and RS-2024-00339116
6 · The paper itself

Abstract

Genome engineering has made remarkable strides, evolving from DNA-binding proteins such as zinc fingers and transcription activator-like effectors to CRISPR-Cas systems. CRISPR technology has revolutionized the field through its simplicity and ability to target specific genome regions via guide RNA and Cas proteins. Progress in CRISPR tools-CRISPR nucleases, base editors and prime editors-has expanded the toolkit to induce targeted insertions or deletions, nucleotide conversions and a wider array of genetic alterations. Nevertheless, variations in editing outcomes across cell types and unintended off-target effects still present substantial hurdles. Artificial intelligence (AI), which has seen rapid advances, provides high-level solutions to these problems. By leveraging large datasets from diverse experiments, AI enhances guide RNA design, predicts off-target activities and improves editing efficiency. In addition, AI aids in discovering and designing novel CRISPR systems beyond natural limitations. These developments provide new modalities essential for the innovation of personalized therapies and help to ensure efficiency, precision and safety. Here we discuss the transformative role of AI in advancing CRISPR technology. We highlight how AI contributes to refining nuclease-based editing, base editing and prime editing. Integrating AI with CRISPR technology enhances existing tools and opens doors to next-generation medicine for gene therapy.

Indexed as

Artificial IntelligenceClustered Regularly Interspaced Short Palindromic RepeatsCRISPR-Cas SystemsGene EditingAnimalsHumansRNA, Guide, CRISPR-Cas SystemsRNA, Guide, CRISPR-Cas Systems

Identifiers

PMID40745000
PMCPMC12322281

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.