AI is making its mark on the pharma market, presenting opportunities for Big Pharma to cut down on drug development costs and fast-track new discoveries. But AI’s capabilities also open the door for smaller biotechs to remain independent rather than leaning on deep-pocketed, established pharmas, according to a report from S&P Global Ratings.
Big Pharma has been investing in AI and partnering with tech companies in recent years, and the area’s value could jump from $1 billion in 2022 to a projected $22 billion in 2027, according to data from Boston Consulting Group.
Many of the early investments in the space were focused on leveraging machine learning. For example, Pfizer teamed up with IBM Watson in 2016 to leverage the company’s machine learning system in drug discovery, while Merck & Co. and AstraZeneca partnered with Amazon Web Services in 2017 to develop a cloud-based drug discovery platform.
But the collaborations between pharmas, tech companies and biotechs have now “given rise to a new breed of AI-driven [biotech] entities,” according to the report.
This new breed has AI at the center of their platforms, but are still partnering with established pharmas to overcome high development costs. Independent AI biotechs will likely seek more partnerships and collaborations as a result, the report predicted, but also have the potential to break out on their own with treatments that could alter the commercial landscape.
“The relationship between AI biotechs and big pharma won't necessarily be symbiotic,” the report stated. “The formers' significant potential for innovation means they could yet emerge as competitors to pharmaceutical incumbents (and Big Pharma's R&D functions).”
Already, several biotechs have drug assets in the clinic that were discovered through AI — both with and without Big Pharma contributions.
Lantern Pharma has several drugs in clinical trials that were discovered through its AI platform. Insilico Medicine has 31 programs and out-licensing agreements for a handful of candidates generated by AI.
AI’s big impact
While S&P didn’t expect that AI will cause an influx of blockbuster drugs, the ratings company forecasted AI biotechs to have a “considerable” impact on shortening the drug development process.
Instead of spending four to seven years in the discovery and preclinical stage, AI could shorten the timeline to two to three years, according to the report. Clinical development could be only three to five years long, shaved down from the current range of seven to nine.
The benefits of speed could help independent biotechs overcome the huge cost challenge of developing new drugs. Between 2022 and 2023, the cost of moving a new drug from discovery to launch averaged $2.3 billion, according to a report from Deloitte.
With an 85% compound annual growth rate projected for the global pharma-AI market, the technology will continue to expand its role across the industry. Still, investments in the space will take time to be fully realized. Instead, the gains are likely to be “incremental,” with efficiencies being slight, the report predicted.
“Drug discovery, with or without AI, will remain a complex and time-consuming practice characterized by experimentation, false starts and failures,” the report stated.
If AI platforms are able to help pharma companies pursue treatments for more complex diseases, working in those complicated arenas could also bog down drug development timelines and increase resource demand, S&P noted.
