, which is developing a machine learning-based approach to engineering genomes, today closed a $100 million funding round. The startup says the funding will be put toward expanding the capabilities of its platforms designed to produce reagents and cells supporting basic research and clinical trials.
Gene engineering is a fraught process involving at least three complex steps. Scientists have to identify the gene they wish to target and material within the gene that’s a prime candidate for removal. They then need to isolate and procure reagents and components for the editing itself, make the edit, and determine whether the edit was performed successfully. That’s one of the reasons gene therapies like Novartis’ Zolgensma, a treatment for Spinal Muscular Atrophy (SMA), cost in excess of hundreds