AI Accelerates Drug Progress, But True Impact Still Years Away
The pharmaceutical industry is rapidly adopting artificial intelligence (AI) to streamline processes, from clinical trial participant selection to report generation, but the full extent of its impact on drug discovery and cost savings remains to be seen. While AI is already delivering tangible benefits,experts suggest it will take one to three years before investors can accurately assess its influence on the speed and efficiency of bringing new drugs to market.
Several major pharmaceutical companies are already experiencing positive results. Novartis, for example, leveraged AI to drastically reduce the time required to select test sites for late-stage clinical trials of its cholesterol-lowering drug, Leqvio. According to Chief Medical Officer shreeram Aradhye, AI cut the selection process from four to six weeks down to just two hours in 2023. Aradhye emphasized that AI is functioning as “augmenting intelligence, not artificial intelligence,” assisting human experts rather than replacing them.
GSK is also utilizing digital tools and AI to accelerate data collection and participant enrollment in clinical trials, aiming for a 15% acceleration. A recent study involving its asthma drug, Exdensur, demonstrated savings of approximately £8 million (roughly $10.1 million USD as of January 26,2024).
Beyond these examples, Genmab plans to integrate Anthropic’s Claude, an AI chatbot, to automate tasks in clinical development and post-trial work, including the creation of graphs, tables, and clinical study reports. ITM,a German radiopharmaceutical company,is exploring AI’s potential to convert lengthy reports into the standardized format required by the FDA,perhaps saving weeks of manual effort.
Despite these advancements, the most critically important potential of AI – drug discovery – is still in its early stages. Amgen Research Chief Jay Bradner believes that molecules discovered with the aid of AI are already in the drug development pipeline, but their success remains to be proven.
TD cowen analyst Brendan Smith cautions that while AI is currently aiding with administrative tasks, a extensive evaluation of its impact on drug development timelines and costs is still some time away.The industry is eagerly awaiting evidence of AI’s ability to identify and develop novel drug candidates, a process that requires extensive research and validation.
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