In the pharmaceutical industry, data has become a strategic asset. Companies are increasingly investing in technologies that enable them to manage, analyze, and derive insights from the enormous amounts of information they generate. As a data strategist, a frequent question I receive is how to build a platform that supports research, monitoring, and evidence generation… Continue reading Internal Data Platforms and Federated Data Models: Understanding the Difference
Category: Methodology
Data Landscaping for Real-World Evidence: A Strategic Framework and Practical Guide
Introduction Data source landscaping is a foundational step in the design and planning of real-world evidence (RWE) studies. It involves identifying, evaluating, and selecting appropriate data sources that align with the study objectives, target population, and operational requirements. With the increasing availability of electronic health data (EHR), claims records, and disease registries, researchers face both… Continue reading Data Landscaping for Real-World Evidence: A Strategic Framework and Practical Guide
How to Learn RWD Research: Insights Beyond the Textbooks
One question I’ve been repeatedly asked is: how do you truly learn to conduct robust and meaningful real-world data (RWD) studies? The answer, in my experience, goes far beyond formal training or academic courses. Unlike traditional clinical trials, which follow well-established and regulated frameworks, real-world research is often shaped by context, data availability, and practical… Continue reading How to Learn RWD Research: Insights Beyond the Textbooks
When the Code Isn’t Enough: Building Diagnostic Algorithms and Proxies in RWD Research
In real-world evidence (RWE) research, misclassification is a persistent methodological challenge, particularly when diagnostic information is incomplete, coded inconsistently, ambiguously recorded or entirely absent. When working with data from secondary data sources such as administrative claims or electronic health records (EHRs), not every condition of interest is captured cleanly (or at all) through a well-defined… Continue reading When the Code Isn’t Enough: Building Diagnostic Algorithms and Proxies in RWD Research
Can Real-World Data Redefine Clinical Trial Protocol Design?
A System Built Backwards? Clinical trials are the gold standard for evaluating new treatments, but they are often built on idealized assumptions that poorly reflect the complexity of real-world clinical care. Protocols are crafted around rigid eligibility criteria, theoretical endpoints, and often over-optimized designs that filter out the majority of patients seen in actual clinical… Continue reading Can Real-World Data Redefine Clinical Trial Protocol Design?