The Convergence of Synthetic Data and Self-Service Analytics to Create a New RWE Model
Webinar Details
Featuring:
Jon D. Morrow, MD, MBA, Senior VP/Medical Affairs & Informatics, MDClone, New York, NY USA (moderator)
Noa Zamstein, PhD, Director of MDClone Research and Data Science Center, MDClone
Henrik Schou, MSc, Vice President, Global Head Evidence Generation at Vifor Pharma
Richard Willke, PhD, Chief Science Officer, ISPOR
Real-world evidence has advanced health research over the past two or three decades. The challenges of procuring sufficient, high-quality real-world data, of unlocking the knowledge contained in the data, and of sharing information without compromising patient privacy are ever-present. Synthetic data, novel data sets that are created to reproduce the statistical properties and interrelationships of the source data, facilitate access to and sharing of real-world evidence on a broader and deeper scale. Self-service analytics allows exploration of data by the primary researchers, without requiring technical intermediaries or specialized knowledge of database structure. Taken together, synthetic data and self-service analytics have the potential to produce major advances in real-world data exploration.
Learning Objectives
Understand the concept of synthetic data, how synthetic data are generated, and how their use facilitates access to real-world, patient-level data without compromising patient privacy.
Understand how self-service analytics tools facilitate research by bringing primary researchers closer to the point of innovation, shortening the time to innovation and discovery.
Understand how the combination of synthetic data and self-service analytics synergistically creates a new model for real-world evidence.
Hosted by ISPOR; Sponsored by MDClone