Data Ownership Drives $750M AI Deals in Life Sciences

Scilex and Altaris led $750M AI-related deals highlighting data ownership in life sciences.

Data ownership is now central to life sciences transactions involving artificial intelligence. A National Law Review article highlights how companies prioritize control over data used in AI-driven research.

Life sciences firms increasingly negotiate detailed terms on data scope, including ownership, usage limits, and access to data generated through collaborations. Harry A. Levin, Associate at Ballard Spahr, explains, "Understanding the legal and commercial implications of data scope, data ownership, and use of data are essential to capturing value and mitigating risk in an evolving landscape." This focus intensifies as AI impacts drug discovery and personalized medicine.

Negotiated AI research structures typically fall into three categories: (1) model owner-led data analysis, (2) the life sciences company as data provider, and (3) joint AI model development. Noelle C. Dubiansky, Partner at Goodwin, poses critical questions: "How does each party protect its proprietary assets? What are their rights to the model outputs and resulting drug candidates or development programs?"

Recent major transactions underscore data’s strategic value. In 2026, Scilex Holding Company invested $150 million in Datavault AI to build supercomputing infrastructure and expand data exchanges in the U.S. Meanwhile, Altaris acquired Clarivate’s Life Sciences & Healthcare division for $600 million. These deals reflect how constrained capital markets push innovation in deal structures and raise the prominence of data ownership issues.

Legal teams face growing challenges defining proprietary data rights used to train AI technologies. Balancing protection of valuable IP with collaboration needs is critical in mergers, acquisitions, and partnerships within life sciences, marking a shift toward data-centric dealmaking.