What if clinical development teams could evaluate potential trial outcomes before a study reaches patients? In this sponsored episode of The Top Line, host Irena Luo speaks with Raja Shankar, vice president for machine learning within AI and technology solutions at IQVIA, about a foundation model designed specifically for life sciences. Shankar explains why general-purpose models may overlook important relationships in patient and clinical trial data and how post-training on life sciences data can make AI more relevant to predictive decision-making. He explores how the model represents patients, diseases, treatments and endpoints, then applies those relationships to anticipate events across a patient journey. The conversation also examines the strategic role of study simulation, including how teams can compare scenarios, challenge assumptions and refine protocol decisions before a trial begins. Shankar addresses the evidence, transparency and expert oversight needed to build confidence in model outputs. Listen to the podcast to learn how simulation could help reduce uncertainty and improve clinical development planning.