Pharmaceutical leader Eli Lilly (LLY.US) has entered into a collaboration agreement with artificial intelligence (AI) startup Profluent, valued at up to $2.25 billion, to explore novel methods for editing DNA. This move represents Lilly's latest bet on AI's potential to transform the drug discovery process. Under the agreement announced on Tuesday, Lilly will secure exclusive rights to new drugs developed by Profluent. Should these drugs achieve specific developmental milestones, Lilly could pay up to $2.25 billion. The initial payment amount was not disclosed, nor were the specific diseases targeted. Typically, developing a new drug takes approximately a decade and costs over $1 billion, with about 90% of candidate drugs failing before final approval. Consequently, the pharmaceutical industry is investing billions in the belief that AI can make drug discovery faster, cheaper, and more successful. While no AI-designed drug has yet received FDA approval, many are currently in clinical trials. Profluent, whose investors include Amazon founder Jeff Bezos, states that its AI can design more powerful versions of CRISPR, the Nobel Prize-winning gene-editing tool. The company aims to treat diseases by inserting large segments of DNA into specific locations—an approach that Profluent's CEO, Madani, claims is not possible with traditional drug discovery methods. Current gene-editing tools are generally limited to correcting small errors in DNA, whereas Profluent's goal is to develop drugs capable of rewriting entire genetic instructions, potentially opening doors to treating a wider range of diseases. Madani remarked in an interview, "This has huge implications for genetic medicines." Similar to how ChatGPT learns from internet text, Profluent has trained its AI models on extensive databases of proteins, which are microscopic molecular machines that perform critical functions in the human body. Profluent's scientists input a target disease into the AI model, and the technology designs a drug that could potentially treat it. As Lilly enjoys significant success from sales of its weight-loss drugs, the company is actively building a pipeline of future treatments to drive its next phase of growth. A key part of this strategy involves increasing its investment in AI. Data shows that over the past five years, Lilly has engaged in at least 15 AI-related deals, more than any other pharmaceutical company. For instance, in January, Lilly partnered with NVIDIA (NVDA.US) to establish a $100 million innovation lab leveraging high-performance supercomputing to tackle pharmaceutical challenges. That same month, Lilly also collaborated with the hot AI startup Chai Discovery—valued at $1.3 billion after a $230 million funding round—to jointly develop AI models aimed at accelerating the discovery of biologics. Last month, Lilly signed another agreement with AI-focused drug developer Insilico Medicine, valued at up to $2.75 billion. Notably, beyond its applications in drug discovery, AI has already delivered a significant, though less publicized, breakthrough for Lilly in the manufacturing sector, specifically for its popular GLP-1 drugs—the weight-loss treatment Zepbound and the diabetes medication Mounjaro. Lilly's Chief Information and Digital Officer, Diogo Rau, previously stated, "Without AI, we absolutely could not have produced as many drugs last year." While he did not provide specific figures, he indicated that the production increase was "substantial enough to materially impact our financial reports." This is critically important for Lilly, as demand for these drugs is exceptionally high, yet the company's production capacity has struggled to keep up. To boost manufacturing capacity for its GLP-1 drugs, Lilly employed a technology called a digital twin, which uses real-time data to create a virtual mirror of a factory, accurately reflecting the operations of the physical plant. This allows the company to test solutions in the digital world before implementing them in reality. The use of digital twins to optimize manufacturing processes is becoming increasingly common. By leveraging AI and digital twin technology, Lilly has significantly enhanced the efficiency of its production processes, achieving drug yields far exceeding those possible with traditional methods. The company modeled every aspect of its factories—from equipment and raw material inputs to production sequences—enabling the digital twin to simulate different configurations and identify the optimal solution. Rau noted, "We thought the results seemed almost too good to be true, but the actual production outcomes matched the digital twin's predictions exactly."
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