A trifecta of newly inked tech partnerships—from Eli Lilly, Bristol Myers Squibb and Incyte—exemplify the increasingly central role that AI is playing in drug development.
Artificial intelligence is quickly becoming a central force in the biopharma industry drug development. On Wednesday, respective AI-centered deals from Eli Lilly, Bristol Myers Squibb and Incyte further embedded advanced machine learning into biopharma world.
BMS partnered with Anthropic, looking to deploy the AI giant’s Claude model across the pharma’s drug development workflow, assisting not just its clinical development and manufacturing operations, but also boosting corporate and commercial functions.
In particular, BMS wants to use Claude to help its data science and engineering units “unlock data and expertise long trapped in the disconnected systems that define biopharma today,” according to a company release.
The pharma also plans to deploy Claude as an agentic aid, helping streamline workflows, synthesize large volumes of data, improve commercial and regulatory engagement and generally lessen the workload for employees.
The BMS partnership is just the latest step that Anthropic is taking to further move deeper into the life sciences game. Last month, for instance, the AI company acquired startup Coefficient Bio for $400 million—though much about the deal, including disease targets and focus modalities, remain under wraps.
Lilly, meanwhile, linked up with Collaborative Drug Discovery, a provider of AI-based data management solutions with a particular focus on the healthcare and life sciences industries.
Through the agreement, the pharma will integrate its own AI engine Lilly TuneLab into CDD Vault, a database hosted and run by Collaborative Drug Discovery that enables the secure sharing of chemical and biological data, assisting biotechs in their respective drug development projects.
Linking the two platforms will allow other participating companies to access “decades of Lilly’s proprietary research data” to train their models, according to the Wednesday release.
“We believe that solving the most complex challenges in drug discovery will depend on innovative collaboration models that provide broad access to research data and empower chemists and biologists to make informed, data-driven decisions,” Barry Bunin, CEO and president of Collaborative Drug Discovery, said in a statement.
Both BMS and Lilly did not disclose financial details of their respective AI agreements.
Also on Wednesday, Incyte expanded its existing collaboration with Genesis Molecular AI, using advanced machine learning models to target yet-undisclosed diseases. The companies first linked up in early 2025 in a pact involving up to three targets.
Now, Incyte is paying $120 million upfront to deepen the relationship and add at least five new targets of Incyte’s choosing. Genesis will be eligible for up to $232 million in milestones for each program. The AI company will also receive royalties on sales of products that make it to the market.
AI has been an increasingly major player in drug development. Earlier this month, AI-forward startup Isomorphic Labs raised $2.1 billion in funding, a raise that analysts say is “the second largest biotech round of all time.” This feat was made all the more impressive by the fact that Isomorphic has yet to disclose a clinical candidate—something that would otherwise drive investors away.
Other experts have also pointed to AI as a major driver behind the uptick in initial public offerings (IPOs) this year, indicating the value that machine learning can have for both companies and investors.
“The companies drawing the most serious investor attention right now, regardless if they’ve IPO’d, share a common characteristic: they’re using AI not just as a discovery accelerator, but as a risk communication tool,” Tyrone Lam, chief business officer at GATC Health, an AI-centric tech-bio company, told BioSpace in an email interview in April.
