Brendan discusses the complexities of gene editing, particularly the challenges of delivering the necessary machinery into cells and identifying off-target effects. He emphasizes the role of machine learning in creating models that can predict how DNA mutations might be compensated, providing insights into potential therapeutic approaches. The conversation also touches on the ongoing research in deep genomics and the evolving landscape of gene editing technologies like CRISPR.
