In Part 2 of our conversation with Matt Truppo, Global Head of Research Platforms and Computational R&D at Sanofi, we move from discovery to development, where the real stakes begin. Matt unpacks the promise and limitations of “digital patient twins,” a concept often described as the holy grail of drug development. With nearly 90% of drugs failing in clinical trials, even modest gains in predicting efficacy or patient response could transform the industry. Through real-world examples, including Dupixent and rare disease therapies, Matt shows how quantitative systems pharmacology (QSP) and AI-driven simulations are already shortening timelines, reducing patient burden, and, in some cases, eliminating the need for entire trials.

But the story doesn’t stop at modeling. We explore how AI is reshaping clinical operations, from Sanofi’s “clinical control tower” that integrates trial data across 4,000 users, to generative AI tools that are cutting regulatory document creation time by more than a third. Matt also shares a personal experiment, building a network of AI agents modeled on his own workflow, reclaiming 30% of his time and offering a glimpse into a more “agentic” future of work. The throughline is clear: AI is not replacing human expertise, but amplifying it, helping the industry finally bend the cost and time curve of drug development.