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Anasayfa » Blog » Drugmakers Turn to AI to Speed Trials and Submissions
Tech

Drugmakers Turn to AI to Speed Trials and Submissions

By ayaksızOcak 27, 2026Yorum yapılmamış2 Mins Read
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Pharmaceutical companies are increasingly using artificial intelligence to accelerate clinical trials and regulatory submissions, even as AI has yet to deliver major breakthroughs in discovering new drugs. Industry executives say the technology is already saving weeks by automating participant recruitment, site selection, and the preparation of vast regulatory documentation.

Executives from major drugmakers including Eli Lilly, AstraZeneca, Roche, and Pfizer said at the JP Morgan Healthcare Conference that AI tools are helping manage thousands of pages of clinical, safety, and manufacturing records required by regulators worldwide.

Drug development can take more than a decade and cost around $2 billion. Companies are betting that AI can improve efficiency and success rates by handling what executives call the “messy middle” of development. Consultancy McKinsey estimates that autonomous, or agentic, AI could lift clinical development productivity by up to 45% over the next five years.

Israeli drugmaker Teva Pharmaceutical Industries said it is using AI to streamline processes so researchers can focus on bringing new medicines to market. Meanwhile, Novartis used AI to cut site selection for a large cardiovascular trial from weeks to hours, helping it hit enrollment targets with minimal overshoot.

Other companies are also reporting tangible savings. GSK said digital and AI tools helped reduce late-stage trial costs by millions of pounds, while Denmark’s Genmab plans to deploy AI agents to automate post-trial analysis and reporting.

While investors are still waiting for the first fully AI-designed blockbuster drug, executives say the technology is already reshaping how trials are run and how data is submitted. Amgen’s research chief said many AI-designed molecules are already moving through pipelines, suggesting the biggest impact may still lie ahead.

Artificial Intelligence clinical trials Drug Development Healthcare pharmaceuticals
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