eSkip-Finder

During the past 10 years, antisense-mediated exon skipping has proven to be a powerful tool for correction of mRNA splicing. For example, recently FDA-approved antisense oligonucleotides, including viltolarsen, eteplirsen, golodirsen, and milasen, were developed based on exon skipping technology. A significant challenge, however, is the difficulty in selecting an optimal target sequence for exon skipping. We have developed a computational method that takes into account many parameters as well as experimental data to design highly effective ASOs for exon skipping1, and improved this frame using a machine-learning algorithm. Shuntaro Chiba and Yasushi Okuno at the Molecular Design Data Intelligence Unit, RIKEN, Dr. Yoshitsugu Aoki at the Department of Molecular Therapy, National Center of Neurology and Psychiatry, and Dr.Toshifumi Yokota at the Department of Medical Genetics, University of Alberta, Faculty of Medicine and Dentistry. 1 Echigoya Y, Mouly V, Garcia L, Yokota T, Duddy W, In Silico Screening Based on Predictive Algorithms as a Design Tool for Exon Skipping Oligonucleotides in Duchenne Muscular Dystrophy.