ReviewFrontiers in genetics2026
Artificial intelligence for precision gene therapy: emerging technologies, clinical applications, and future directions.
Review in Frontiers in genetics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
2 authors.
Funding
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Abstract
Artificial Intelligence (AI) is revolutionizing gene therapy from an empirical and iterative process to a predictive, data-driven and increasingly intelligent therapeutic development approach. This review covers the application of AI extensively throughout the gene therapy development process, from target therapeutic discovery, identification of disease genes, variant interpretation, integration of multi-omics data, optimization of CRISPR, engineering of the vector, prediction of immunogenicity, manufacturing, and clinical development and post-marketing surveillance. The role of machine learning, deep learning, foundation models, generative AI and digital twins for advancing therapeutic design, boosting vector performance, manufacturing optimization, patient stratification and enabling precision medicine is discussed. Lastly, we provide directions for future research and highlight the need for close multidisciplinary cooperation between computational scientists, biologists, clinicians, industry, and regulatory agencies to facilitate the development of safe, effective and personalized genetic medicines responsibly.
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Registered trials
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 Socratic graph.