Big Pharma is investing heavily in AI to slash development timelines and foster innovation. But instead of strengthening future relationships with the biotech world, the investment may position independent AI-focused biotechs as a threat to pharma’s internal R&D processes.
The relationship between AI-focused biotechs and Big Pharma “won't necessarily be symbiotic,” according to an Oct. 1 report from S&P Global.
The global pharma-AI market was valued at $1 billion in 2022, a figure expected to swell to nearly $22 billion by 2027, according to 2023 data from the Boston Consulting Group.
This significant investment in the space could enable large pharmas to establish long-lasting competitive advantages over smaller rivals, according to S&P.
Early AI adoption in the industry was characterized by Big Pharma’s deployment of machine learning systems from tech companies, such as Pfizer’s 2016 partnership with IBM Watson or Novartis' 2018 collaboration with Microsoft. Since then, pharma has also plucked biotech partners to provide their AI tech, such as the deals between AstraZeneca/BenevolentAI and GSK/Insilico Medicine.
These pharmas, plus others like Roche, Sanofi and Eli Lilly, have established an AI foundation at least in part through tech or biotech companies.
Meanwhile, the “newer breed” of biotechs with AI at the heart of their R&D platforms are still dependent on Big Pharmas, often via funding in exchange for a share of pipeline wins, according to the S&P analysts.
Independent AI-focused biotechs' smaller size will often mean they lack the investment firepower necessary to move treatments through approval and market launch. This will likely necessitate partnerships with external companies, such as pharmas, CROs or CDMOs, S&P said.
Overall, S&P analysts don’t believe AI will produce more blockbuster drugs, but instead help cut down on development timelines. Current AI drug discovery efforts take an average of two to three years, compared to four to seven years for those without AI.
Clinical development timelines using the novel tech run around three to five years, instead of the average seven to nine years without, according to S&P.
In particular, AI has been used for oncology and neurology R&D, which reflects the urgency to address critical health issues more quickly, according to S&P.
All this being said, the advantages of AI in biopharma R&D will take years to fully materialize and will depend on continued investment, willingness to adopt new processes and the ability to manage change, S&P said in its report.