Profluent and Eli Lilly Forge $2.25 Billion AI Gene Editing Partnership

# Profluent and Eli Lilly Forge $2.25 Billion AI Gene Editing Partnership

Eli Lilly has placed one of the largest bets yet on artificial intelligence in drug development, signing a deal worth up to $2.25 billion with Berkeley-based startup Profluent to design novel gene editing proteins using machine learning. The partnership, announced Monday, tasks Profluent's AI platform with creating custom recombinase enzymes capable of inserting entire genes at precise locations in the human genome — a technical feat that remains beyond the reach of conventional CRISPR-based editing systems.

Under the multi-program research collaboration, Profluent will use its generative AI models to design site-specific recombinases for multiple genomic targets tied to diseases with severe unmet medical needs. Lilly will then take the lead on preclinical development, clinical trials, regulatory approvals, and commercialization. Profluent receives an undisclosed upfront payment and committed research and development funding, with eligibility for up to $2.25 billion in development and commercial milestone payments plus tiered royalties on future net sales.

The deal centers on what both companies describe as a holy grail in genetic medicine: kilobase-scale DNA editing. While CRISPR and base editing technologies excel at making small, targeted changes to DNA — knocking out genes or swapping individual nucleotide bases — they struggle to insert long stretches of genetic material, sometimes entire genes, at specific locations. Recombinases, a class of enzymes that can cut, rearrange, and insert large DNA sequences, offer a potential solution. The problem is that naturally occurring recombinases rarely target the exact genomic locations needed for therapeutic purposes.

That is where Profluent's AI enters the picture. The company's machine learning platform, trained on what it calls the world's largest protein dataset including the most comprehensive database of naturally occurring recombinases, generates entirely novel protein designs programmed to target precise locations in the genome.

"Kilobase-scale DNA editing remains a holy grail in genetic medicine," said Ali Madani, co-founder and CEO of Profluent. "Our work with Lilly is aimed at unlocking therapeutics previously thought impossible. We believe only AI can create the designer recombinases needed to precisely target any location in the genome. This collaboration with Lilly demonstrates that our platform is ready to build the toolkit needed to scale genetic medicines."

Profluent's Chief Business Officer Hilary Eaton framed the partnership as addressing a fundamental gap in the gene editing field. "Standard knock-out and base editing approaches leave entire categories of disease out of reach," Eaton said. "Kilobase-scale DNA editing is how we reach them — and Profluent's generative models were built for exactly this problem."

The deal marks Profluent's first partnership with a major pharmaceutical company and comes five months after the startup closed a $106 million funding round co-led by Bezos Expeditions — the personal investment vehicle of Jeff Bezos — alongside Altimeter Capital, Spark Capital, Insight Partners, and Air Street Capital. For Lilly, it represents the latest in a series of aggressive moves into genetic medicine. The Indianapolis-based pharma giant, flush with record revenues from blockbuster obesity and diabetes drugs Mounjaro and Zepbound, has opened a dedicated genetic medicine center in Boston and acquired multiple gene editing and gene therapy companies in recent years. According to Endpoints News, this is Lilly's second recombinase-focused partnership of 2026 alone.

The $2.25 billion headline figure places the Profluent deal among the largest AI-driven drug development collaborations to date and signals growing pharmaceutical industry confidence that machine learning can accelerate the notoriously slow and expensive process of bringing new therapies to patients. Traditional drug development timelines of 10 to 15 years and costs exceeding $2 billion per approved drug have made the industry hungry for AI-powered shortcuts. Deals like this one suggest that big pharma increasingly views AI not as a speculative technology but as a practical tool for tackling biological problems that have resisted conventional approaches.

The partnership also reflects a broader maturation in the AI-for-biology space. While early AI drug discovery companies focused primarily on small molecule design and target identification, a new wave of startups like Profluent is applying generative models to protein engineering — designing biological tools from scratch rather than merely screening existing compounds. If Profluent's AI-designed recombinases prove effective in clinical settings, the implications could extend well beyond this single partnership, potentially opening the door to programmable gene insertion therapies across hundreds of genetic diseases currently considered untreatable.

The collaboration carries meaningful risk. AI-designed proteins remain largely unproven in human clinical trials, and the leap from computationally generated enzyme designs to safe, effective therapies in patients is enormous. But with Lilly's deep clinical development expertise and Profluent's novel AI platform, the partnership represents a credible attempt at cracking one of genetic medicine's most stubborn challenges. The coming years will determine whether the holy grail of kilobase-scale gene editing moves from computational promise to clinical reality.