Jacob Tome leads the Enhancer Design Flywheel Team within AI BioDesign. The team's goal is to solve the training-data sparsity problem for machine learning models of gene regulation by generating high-quality data at scale, tailored to the frontier where those models are most uncertain and where improvement would be most impactful. His background is in leveraging biochemistry to develop novel sequencing assays for understanding gene regulation, and in high-throughput screens that enable synthetic biology at scale. He completed his PhD with John Lis at Cornell University, where he hacked an old Illumina sequencer to measure binding affinities on the flow cell and developed new versions of nascent-RNA run-on sequencing. He did a postdoc with Jay Shendure where he learned MPRAs and synthetic biology. Most recently, at Shape Therapeutics, he engineered cell type specific enhancers for gene therapy payloads. He then stepped in to lead the readout of Shape's final AAV capsid screen and took the program through the validation study that delivered DB1, a blood-brain-barrier-crossing capsid. This was a deeply collaborative effort balancing computational, high-throughput wet lab, and translational teams, very much in the same vein as AI BioDesign.