Artificial intelligence for precision gene therapy: emerging technologies, clinical applications, and future directions.

AI-driven methods are transforming gene therapy development into a predictive, data-driven process across multiple stages, from target discovery to post-marketing surveillance.

• Why it matters: This shift addresses the need for more precise, efficient, and personalized genetic medicines, bridging gaps between empirical approaches and tailored treatments.
• What they did: The review discusses the application of AI—including machine learning, deep learning, foundation models, generative AI, and digital twins—in areas such as disease gene identification, variant interpretation, vector engineering, immunogenicity prediction, manufacturing, and clinical trials, emphasizing the importance of multidisciplinary collaboration.
• The result: Integrating AI technologies may enhance therapeutic design, vector performance, manufacturing efficiency, and patient stratification, ultimately enabling safer, more effective, and personalized gene therapies.