Abstract :

Hemophilia is the most frequent severe genetic haemorrhagic condition. Hemophilia A and B are caused by a lack or dysfunction of the factor VIII and factor IX proteins, respectively, and are distinguished by prolonged and heavy bleeding after minor trauma or even spontaneously. Treatments for hemophilia have been extremely expensive and required the infusion of plasma clotting factors throughout one’s life. The last few years have brought major breakthroughs in gene therapy that now hold real promise for possible curative options. Artificial intelligence has the potential to transform all levels of hemophilia gene therapy, from vector design to predictive modeling and biomarker identification. This review highlights selected applications of AI towards precision medicine including viral vector design, predictive modeling for gene editing, and deep phenotyping in hemophilia gene therapy. It can greatly improve the efficacy and safety of gene therapy through off-target effects prediction, optimization designs of delivery vectors, and determination of personalized combinations of treatments. Consequently, this will also enable accelerated biomarker development for disease diagnosis and monitoring. In such a way, artificial intelligence in hemophilia gene therapy will revolutionize the framework of treatment and make it personalized or even curative for patients all over the world.

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Keywords :

deep learning and machine learning., gene editing, gene therapy, Hemophilia, viral vectors

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