<p>Profluent just announced a multi-program strategic partnership with Eli Lilly to develop AI-designed recombinases for genetic medicine — worth up to $2.25 billion in milestones, plus tiered royalties on net sales.</p><p>In this episode, Nathan unpacks why this deal matters far beyond the headline number. CRISPR taught us how to fix typos in the genome. The harder problem — and arguably the larger one — is editing at the kilobase scale: replacing whole paragraphs of DNA at a chosen genomic address. That&#39;s the route to therapies for the long tail of genetic disease driven by patient-level mutational heterogeneity, from cystic fibrosis to inherited hearing loss to retinal dystrophy.</p><p>Recombinases have always been the right class of enzyme for this job. They&#39;ve also been stuck for decades because their targeting specificity is encoded directly in the protein structure, with no equivalent of CRISPR&#39;s modular guide RNA. That makes recombinases a near-perfect problem for foundation-model protein design — and it&#39;s exactly the bet Profluent has been building toward since their 2024 work designing novel Cas enzymes from scratch.</p><p>We cover: why kilobase-scale editing is the next frontier of genetic medicine; why recombinases were intractable until AI; how Profluent&#39;s foundation-model platform changes the picture; why Lilly is the right partner; and what the world looks like if you can name a genomic address and get a designed editor back.</p>