DATA LANDSCAPING

 

 

I conduct structured and systematic data source landscaping to identify the most relevant real-world data (RWD) sources for a given scientific or regulatory question. This step is critical in building a strong foundation for any real-world evidence (RWE) strategy, ensuring that study design is grounded in a clear understanding of what data actually exists and how usable it is.

 

My methodology integrates targeted literature review, landscape assessments of disease areas, and mapping of available data assets across multiple regions (US/CAN, EU, APAC). I evaluate a broad range of sources including claims databases, electronic health records, disease registries, hospital systems, and emerging hybrid or linked datasets.

 

A key strength of my approach is access to a well-established network of data vendors and data custodians, which enables rapid clarification of data availability, structure, and limitations. In many cases, I am able to directly engage with trusted partners to validate feasibility assumptions, resolve data uncertainties, and accelerate decision-making timelines.

 

The output of this process is a structured evidence landscape that not only identifies “what exists,” but also assesses accessibility, usability, and scientific relevance. This ensures that downstream feasibility assessment, study design, and operational planning are built on a solid and realistic data foundation.