Researchers at the University of Zurich have developed an artificial intelligence-based tool named Pythia to predict DNA repair outcomes following CRISPR/Cas9 editing. This deep learning-assisted design of microhomology-based repair templates markedly improves precise genome integrations, overcoming challenges in control of DNA repair mechanisms that often lead to unintended genetic alterations. This advancement enhances the accuracy and predictability of gene editing therapies in human cells and animal models, promising safer clinical applications for genetic diseases and research.