The evolution of AI in clinical development is increasingly a story of action, not only insight. Predictive models helped teams identify risks and data-quality issues, and generative AI made complex information easier to explore. Agentic AI introduces a more consequential question: which parts of a clinical workflow can technology responsibly take on?
In this sponsored episode of The Top Line, Saama leaders Ari Srinivasan and Yatesh Midha examine that question through the lens of AgentOS, an orchestration and governance layer for specialized clinical tools, skills, agents and workflows. Their discussion moves from architecture to practice, including how agents could retrieve evidence, reconcile records across systems and surface discrepancies for expert review.
The promise is not autonomy without limits. It depends on task-appropriate models, grounded results, clear provenance, permission controls and human responsibility for consequential judgments. The broader opportunity is to shift clinical professionals away from repetitive comparison work and toward the exceptions and decisions that require experience. Listen to the full interview to learn more.