Data is emerging as a central factor in biopharma transactions, especially the digital information used to train artificial intelligence models for drug target selection. As major deals are signed, companies focused on AI-driven drug discovery face complex negotiations to ensure continued access to essential data, while pharmaceutical firms adjust their strategies to participate in these collaborations.
Chad Diehl, legal team lead for licensing and acquisitions at Astellas Pharma, commented during a panel discussion at the BIO International Convention last month, “I just turn on my ‘out of office’ when I hear a data deal is coming.” Deepa Talpade, head of business development and licensing for oncology at Bayer, said that pharmaceutical companies have traditionally sought strict control over partnership-generated data. However, she said that details such as which chemistry lab is used or where the data is physically generated are now important considerations during deal signing.
Previously, biotech platform companies would transfer most of the partnership-generated data during licensing deals while keeping programs siloed. These learnings were typically used to improve platforms but not fed back into computers for use in other projects. This approach has shifted as AI-focused firms require broader access to information. “Those types of deals are not going to fly these days when we’re thinking about AI-focused deals,” said Rachel Lane, senior vice president of business development and operations at Xaira Therapeutics.
Lane explained that Xaira views partnerships as opportunities to access new datasets unavailable internally. She added that both sides need each other: biotechs need partnerships with larger pharma firms to validate their concepts and advance research efforts. “One plus one equals five in the context of the deal,” Lane said.
Pharmaceutical companies are responding by forming new alliances with AI specialists. Merck recently signed an agreement with Protillion Biosciences worth $510 million upfront; Eli Lilly, Bristol Myers Squibb, and Incyte have also made similar arrangements with AI firms this year. Lilly has expanded its own capabilities by launching TuneLab last year—a program offering select biotechs access to its proprietary AI suite in exchange for shared datasets.
Maha Radhakrishnan, executive partner at Sofinnova Investments who has been involved in numerous industry deals, emphasized the importance of professional guidance when addressing issues related to AI data ownership and usage: “That’s where we get the patent attorneys, legal teams involved to make sure that there’s clarity from the get-go.”
