Sanofi aims to cut AI-driven drug development timelines in half with Snowflake
The pharmaceutical industry’s research and development marathon — stretching 10 to 12 years from hypothesis to approval — is set to shrink as AI-driven drug development compresses that timeline.
The shift from AI experimentation to real transformation of business workflows is accelerating across industries, but few examples carry higher stakes than pharma, where a drug’s failure at phase three of a clinical trial means patients have been waiting nearly a decade for nothing. Governing data at enterprise scale is the prerequisite, according to Emmanuel Frenehard (pictured, left), chief digital officer of Sanofi S.A.
“We believe, I believe, that we’ll be able to see and we’re starting to simulate even clinical trials before they happen,” Frenehard said. “So we still have to do them, but we do them with more precision. We do them with a better appreciation of the kind of patients we need in those trials. My intention is to have the time it takes — so from 10 to 12 to five to six.”
Frenehard and Dayne Turbitt (pictured, right), senior vice president of EMEA at Snowflake Inc., spoke with theCUBE’s Dave Vellante and Rebecca Knight at Snowflake Summit 2026, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed AI-driven drug development, agentic workflows and how a unified data foundation enables AI to reinvent enterprise processes.
