Unlocking Bigger Insights: Innovative Techniques for Combining Real World Datasets

In our previous blog post, we highlighted the clinically-rich nature of the PHARMO Data Network, which can be leveraged to generate real world evidence (RWE) in rare diseases. We know this can be challenging due to multiple factors, such as the need for multiple diagnostic criteria for diagnosis, the requirement for longitudinal data across multiple settings of care and, most significantly, the limited sample sizes of patients within a single dataset. To overcome challenges with sample sizes, pooling datasets is one possible solution. However, pooling datasets can be undertaken in multiple forms and varying complexities. The three common approaches we explore in this article are 1. Harmonization of scientific methods, 2. Pooling of aggregate results, and 3. Pooling of individual patient-level data.