The landscape of RWD can be difficult to navigate.

Database mapping provides a tool to systematically identify and evaluate RWD sources.

Real world data (RWD) has the potential to inform drug development, drug regulation, health technology assessments, and to refine clinical guidelines by characterising a product’s clinical outcomes in more diverse, real world patient populations. RWD sources are wide ranging, from national and regional registries, electronic medical records, claims databases, health surveys, to clinical databases. The growth and heterogeneity of RWD sources has created a data landscape that is increasingly difficult to navigate; identifying data sources to help answer strategic or study objectives is not always an obvious choice.

Database mapping is a flexible methodology that can be customized to meet various needs, whether to locate data sources to answer a specific study question or to get a larger overview of RWD sources for an indication of interest. Join us to learn:

  • What a database mapping is and where it can be useful
  • The components of a database mapping and how to tailor these to meet your specific objectives
  • A use case for database mapping in the field of oncology to identify clinico-genomic databases


This webinar is intended for professionals from pharmaceutical, biotech, and medical device companies involved in:

  • Epidemiology
  • Health economics & outcomes research
  • Marketing
  • Market access
  • Medical affairs
  • Real world evidence
  • Regulatory affairs
  • Clinical outcomes


Ekaterina Maslova, ScD

Senior Epidemiologist, Real World Evidence Strategy and Analytics, ICON plc.

Ekaterina is an epidemiologist with over 10 years of experience in epidemiological research and public health, working with large longitudinal data sets of self-reported, clinical, and biomarker data as well as national disease and prescription registries in the US, UK, and Nordic countries. She has extensive expertise in study design and conceptualization; advanced epidemiologic methods; data collation and analysis; and dissemination into the scientific community. At ICON, Ekaterina is responsible for designing, leading, and analysing observational studies, including retrospective database studies, prospective cohort studies, referral studies, and quality improvement studies in a variety of indications.

Ruchika Sharma, BDS, MPH

Analyst II, Real World Evidence Strategy and Analytics, ICON plc.

Ruchika Sharma has over 6 years of experience encompassing epidemiology, public health, and health care. At ICON, Ruchika has worked in multiple database mapping and feasibility studies across Europe, North America and Asia-Pacific. She has extensive experience on literature review, disease forecasting techniques, risk-factor modeling, patient-population sizing, epidemiological methods and study design with expertise on analyzing large population-based databases like HCUP, NHANES, SEER and NSSO. Ruchika has worked on a variety of therapeutic areas like infectious diseases, neurology, oncology, cardiovascular diseases, metabolic disorders, immunology and respiratory diseases.

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