Pharma has spent years investing in more data, more vendors, and more analytics. Yet teams still struggle to find the right patients fast enough for modern clinical and commercial demands.
Why? Because many traditional approaches are built on delayed or clinically flattened signals. Claims can show that something happened. They rarely capture the full clinical intent behind why it happened, whether a patient truly meets nuanced criteria, or where an intervention window is opening in real time.
In an era of targeted therapies, tighter eligibility criteria, enrollment pressure, and growing scrutiny around evidence quality, that gap matters. This session will examine where legacy methods fall short, why more data alone is not solving the problem, and what it takes to build a more precise, clinically grounded patient identification strategy.
Learning Objectives:
• Identify the hidden limitations of traditional patient identification strategies that rely on retrospective or clinically flattened data signals.
• Understand how gaps in patient visibility impact trial recruitment, evidence quality, and commercial launch readiness.
• Evaluate how clinically grounded patient identification approaches can improve precision, speed, and strategic decision-making across the drug lifecycle.