General-purpose AI can identify broad patterns, but clinical development demands models that understand the complex relationships within life sciences data. In this sponsored episode of The Top Line, IQVIA’s Raja Shankar examines how a foundation model trained on life sciences data can support more predictive, evidence-based decision-making.
The discussion explores how study simulation combines real-world patient data, rich biomedical information and scientific expertise to model potential outcomes before a study begins. By comparing scenarios early, teams can refine protocol choices, assess trade-offs and make more informed decisions before committing time, budget and patient participation.
Shankar also considers what it takes to build confidence in these tools, from benchmarking predictions against historical trials to giving subject matter experts transparent reasoning they can evaluate. Listen to the podcast to learn how simulation may help reduce uncertainty and strengthen clinical development strategy.