Addressing Heterogeneity, Enhancing Confidence: The Benefits of Common Programming and Centralized Analysis

Why do harmonized protocols still lead to heterogeneous results and how can we do better?

Regulatory agencies like the European Medicines Agency (EMA) and US Food and Drug Administration (FDA) increasingly encourage the use of real world data (RWD) to generate real world evidence (RWE) for both initial drug approvals and post-authorization requirements. The EMA’s third annual report on integrating RWE showed that a total of 59 studies utilizing RWE were conducted between February 2024 and February 2025 which is a 47% increase in studies using RWD to support regulatory decisions compared to the previous year.1

Evaluating the long-term safety of approved medicines is one of the key research areas where RWE plays an important role. These scientific programs aim to generate a comprehensive understanding of a product’s safety profile across diverse patient populations and myriad healthcare systems. To achieve this, studies often rely on data from multiple countries. While this approach enhances the robustness of findings, it also requires data standardization and methodological consistency to ensure results are comparable and reliable. Although pooling person-level data (PLD) across countries might seem like a logical step to maximize analytical power, it is often not straightforward. Key challenges include compliance with General Data Protection Regulation (GDPR) and local ethics/data governance regulations, which can restrict cross-border data sharing. Moreover, there can be value in retaining and analysing data at the country level, allowing for insights that are context-specific and relevant to local healthcare decision-making.