AI-Designed Drug Enters Phase III in Just Four Years: Generate Biomedicines Highlights Speed and Potential of AI in Drug Development as MNCs Ramp Up Investments

The STAR Market Daily, December 2ndHow long does it take for an AI-aided designed innovative drug to progress from concept validation to Phase III clinical trials?

An AI pharmaceutical company from the United States has provided an answer. Recently, biotechnology company Generate: Biomedicines announced that its AI-engineered TSLP-targeting monoclonal antibody drug GB-0895 will initiate two Phase III clinical trials.It only took four years from the early stage of development.In contrast, another TSLP monoclonal antibody, Tezepelumab, took nearly six years to enter Phase III clinical trials since its development began in 2012.

Data shows that GB-0895 is expected to be used for the treatment of severe asthma and chronic obstructive pulmonary disease (COPD). Two research programs plan to recruit 1,600 patients with severe asthma. At the 2025 European Respiratory Society (ERS) International Congress, Generate reported Phase I study data of GB-0895 for asthma. The results showed good overall tolerability, a half-life of 89 days, and the ability to continuously reduce key biomarkers, enabling a long-acting therapy with dosing every six months.

Mike Nally, CEO of Generate, stated: "This is a significant milestone for both the company and the entire industry. It demonstrates how antibodies designed using artificial intelligence can achieve what may be the best performance in their class, and how they can advance to Phase III clinical trials within just four years."

It is worth mentioning that,Generate secured investment from NVIDIA in its $273 million Series C funding round.The latter has been continuously expanding its presence in the AI pharmaceuticals field in recent years: On October 28, it announced a collaboration with global pharmaceutical giant Eli Lilly to build the largest AI pharmaceutical factory, equipped with the NVIDIA DGX SuperPOD featuring the DGX B300 system. In addition, through its investment arm, it has participated in the financing of several AI pharmaceutical companies, including Lambic and Charm.

▌AI-Driven Pharmaceutical BD Transactions Are Heating Up

Not only Nvidia, but in recent times, MNCs have successively increased their investments in AI drug discovery.

On November 20, biotechnology company Valo Health announced a strategic partnership with Merck, which plans to utilize the former’s artificial intelligence platform to rapidly generate preclinical compounds. The collaboration includes an upfront payment and potential milestone payments totaling over $3 billion, along with royalties and research funding.

On November 10, Insilico Medicine and Eli Lilly entered into a strategic drug discovery collaboration. Eli Lilly will leverage Insilico Medicine's self-developed AI drug discovery platform, Pharma.AI, to accelerate the discovery and development of innovative therapies. Under the agreement, Insilico Medicine is entitled to receive up to over $100 million in total payments from this collaboration, including upfront payments, research and development milestone payments, and tiered royalties on net sales upon future commercialization of the drug.

On November 5, Ailux, a wholly-owned subsidiary of XtalPi, reached a multi-target strategic cooperation and platform licensing agreement with Eli Lilly, with a total value of up to $345 million. Eli Lilly will leverage Ailux's proprietary platform to accelerate the discovery and development of bispecific antibodies across multiple therapeutic areas, while utilizing its AI antibody R&D platform to expedite internal pipeline research.

According toGuoJin SecuritiesStatistics,By 2025, AI Pharmaceutical BD Has Reached 12 Items. The agency believes that, whether in China or in Europe and the United States, regulatory support for cutting-edge innovation in the pharmaceutical field will increase in multiple dimensions. The strategic positioning in disruptive innovation technology sectors will be a key battleground for pharmaceutical companies in the future. Frontier sectors, including AI drug development, could become new hotspots by 2026.

Shanghai Securities stated that relevant policies for AI + healthcare had been successively introduced. Compared with traditional drug research and development, AI technology can process multi-dimensional and complex data such as genomics, proteomics, and metabolomics, and use data mining and pattern recognition technologies to discover potential targets, promoting the research and development of First-in-class innovative drugs. In 2023, the market size of AI + healthcare in China was 8.8 billion yuan, and it is expected to reach 315.8 billion yuan by 2033, with a compound annual growth rate of 43%.