Using Real-World Data to Identify Barriers to Treatment Adoption

Understanding how and why new therapies are adopted—or not adopted—in real-world practice is critical to advancing precision medicine. While clinical trials may demonstrate efficacy, real-world adoption is shaped by far more complex factors, including diagnostic timing, provider behavior, and care coordination. Real-world data, especially when structured into patient journey analyses, is emerging as a key tool for illuminating these patterns and identifying actionable barriers to treatment uptake.Adoption is rarely uniform when new targeted therapies are introduced into routine clinical care. Despite strong clinical data, some therapies experience slower uptake across sites, regions, or patient groups. The therapies themselves don’t always drive these differences. Instead, they often reflect diagnostic workflows, coordination gaps, and physician decision-making.