The Impact of Artificial Intelligence in Gene Therapy

Artificial intelligence (AI) is revolutionizing the field of gene therapy by enabling more precise, efficient, and personalized treatments. AI tools, particularly machine learning (ML) and deep learning (DL) algorithms, are being leveraged to analyze large genomic datasets, identify potential gene targets, and predict the outcomes of genetic modifications. These AI-driven approaches can optimize gene editing techniques like CRISPR-Cas9 by predicting off-target effects and improving editing accuracy. Moreover, AI enhances the design of gene delivery systems, aiding in the development of safer and more effective vectors for gene transfer. In the realm of personalized medicine, AI is crucial in identifying patient-specific genetic variations that can influence treatment outcomes, enabling tailored therapies. Additionally, AI models are being used to monitor and assess long-term effects of gene therapy, allowing for adaptive strategies and real-time adjustments in clinical trials. Despite challenges, such as data quality and algorithm transparency, the integration of AI into gene therapy holds promise for accelerating the development of groundbreaking treatments for genetic disorders, offering new hope for precision medicine. As AI continues to evolve, its role in gene therapy will likely become increasingly integral to transforming medical practice.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-11-28
DOI
https://doi.org/10.5281/zenodo.14233535
Primary Topic
Virus-based gene therapy research
Type
article
Field-Weighted Citation Impact
0.00
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article

The Impact of Artificial Intelligence in Gene Therapy

Zenodo (CERN European Organization for Nuclear Research)
Virus-based gene therapy research
article

The Impact of Artificial Intelligence in Gene Therapy

article en

Abstract

Artificial intelligence (AI) is revolutionizing the field of gene therapy by enabling more precise, efficient, and personalized treatments. AI tools, particularly machine learning (ML) and deep learning (DL) algorithms, are being leveraged to analyze large genomic datasets, identify potential gene targets, and predict the outcomes of genetic modifications. These AI-driven approaches can optimize gene editing techniques like CRISPR-Cas9 by predicting off-target effects and improving editing accuracy. Moreover, AI enhances the design of gene delivery systems, aiding in the development of safer and more effective vectors for gene transfer. In the realm of personalized medicine, AI is crucial in identifying patient-specific genetic variations that can influence treatment outcomes, enabling tailored therapies. Additionally, AI models are being used to monitor and assess long-term effects of gene therapy, allowing for adaptive strategies and real-time adjustments in clinical trials. Despite challenges, such as data quality and algorithm transparency, the integration of AI into gene therapy holds promise for accelerating the development of groundbreaking treatments for genetic disorders, offering new hope for precision medicine. As AI continues to evolve, its role in gene therapy will likely become increasingly integral to transforming medical practice.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 55%
Virus-based gene therapy research
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The Impact of Artificial Intelligence in Gene Therapy · Zenodo (CERN European Organization for Nuclear Research) (2024) | TGRS Research Map | TGRS