Inside the AI Rush Reshaping US Biotech

Nabla Bio and Takeda expand their second AI biologics deal as momentum grows and biotech firms rush to modernize discovery

15 Oct 2025

AI-driven drug discovery is gaining momentum in the US as Takeda and Nabla Bio broaden their second collaboration, first launched in 2022, in a move seen by analysts as a marker of rapid change across biologics research.

The companies said in an October announcement that the expanded agreement includes double-digit millions in upfront and research payments and more than $1bn in potential milestone fees. The deal aims to speed development of Nabla Bio’s platform, which designs protein-based drug candidates in a matter of weeks, a process that traditionally takes years.

Industry advisers view the partnership as part of a wider effort by drugmakers to modernise early-stage research. One strategy consultant said organisations were increasingly under pressure to shorten development cycles while maintaining scientific standards. Nabla Bio executives added that combining AI with high-throughput laboratory testing could ease long-standing bottlenecks in biologics development.

Falling sequencing costs and wider access to molecular datasets have created favourable conditions for advanced modelling tools. Market researchers expect strong growth for companies building AI-centred platforms, while a series of partnerships and acquisitions is reshaping the competitive landscape. The US Food and Drug Administration is preparing guidance on the use of AI in early discovery to ensure safety and transparency as algorithms become more central to research.

Uncertainties persist. Some scientists argue that molecules designed by AI must still demonstrate clear value in clinical testing. Others point to unresolved questions around intellectual property when algorithms produce entirely new structures. But many experts believe these issues can be managed through existing regulatory and legal frameworks.

The strengthened Takeda–Nabla Bio alliance highlights how drugmakers are moving away from slower trial-and-error approaches toward automated and data-rich methods. If emerging results continue to hold, AI-designed biologics could accelerate development timelines and broaden options for new therapies.