Pharmaceutical Companies Adopt AI to Accelerate Clinical Trials and Regulatory Approvals

Artificial intelligence is transforming the pharmaceutical industry by streamlining labor-intensive parts of drug development, even if it has yet to fully deliver on discovering breakthrough molecules. Industry executives report that AI is helping with clinical trial site selection, participant enrollment, and regulatory document preparation, reducing weeks of manual work. Bringing a new drug to market typically takes a decade and around $2 billion, prompting companies like Eli Lilly, in partnership with Nvidia, to explore AI as a way to improve success rates.

Consultancy McKinsey predicts that autonomous, agentic AI could increase clinical development productivity by 35% to 45% over the next five years. Israel-based Teva Pharmaceutical Industries is leveraging AI to focus on the core goal of developing successful drugs, while automating administrative tasks such as digitization, process improvement, and modernization.

Executives from AstraZeneca, Roche, Pfizer, and smaller biotechs like Spyre and Nuvalent highlighted the challenge of tracking thousands of pages of clinical, safety, and manufacturing documents for regulators. These documents must be compiled, cross-checked, and kept consistent across regions, often requiring costly external contractors. Venture capitalists, including Andreessen Horowitz, are investing in startups like Alleviate Health, which uses AI to improve patient outreach, education, screening, and scheduling to reduce dropouts in clinical trials.

Large language models, such as Microsoft Copilot, are increasingly used for administrative tasks, but analysts note that measurable impact on drug development timelines may take one to three years. Novartis applied AI in 2023 for a 14,000-person cardiovascular outcomes trial, reducing site selection from four to six weeks down to a two-hour process and closing enrollment with minimal overages. AI in this case acted as augmenting intelligence, speeding up operations without replacing human decision-making.

GSK has implemented AI and digital tools to cut manual data work and accelerate trial enrollment, saving approximately $10.87 million in late-stage asthma studies for its drug Exdensur. Genmab plans to use Anthropic’s Claude chatbot-powered AI to automate post-trial data analysis, transforming results into tables, graphs, and clinical study reports. German firm ITM has applied AI to convert lengthy trial reports into FDA-compliant templates, potentially saving weeks of staff time. Amgen research chief Jay Bradner emphasized that while AI is improving drug development workflows and regulatory preparation, the pharmaceutical industry is still awaiting AI-designed molecules, which are reportedly already in pipelines.

Overall, AI is improving efficiency, reducing costs, and accelerating administrative aspects of clinical trials, while the search for AI-discovered drugs continues in research pipelines.