The promise of real-world data lies in its high external validity for characterizing patient experience as it exists in real life, across a heterogeneous breadth of diseases, patient types, and treatments.  With this breadth comes the challenge of understanding and comparing findings between studies conducted by different researchers, in different datasets, or at different times. 

This webinar will address how the use of technology for deploying data and analytic standards can be utilized to meet this challenge, by facilitating the standardization, transparency, reproducibility, and replicability of RWD research. Examples and Use Cases will be shared to illustrate how this approach greatly enhances rapid iteration of analytical methods and boosts confidence in research results.

Featured Speakers

Bruno Lempernesse

VP & General Manager, Real World Evidence Solutions
Acorn AI, a Medidata Company

Bruno leads Acorn AI’s evidence strategy along with a team of experts in RWD, RWE, and data science. With over 25 years of experience in the life sciences industry, Bruno has held several leadership roles in healthcare technology solutions, RWE, and data science/analytics at global levels. 

Aaron Galaznik, MD

VP of Research, Real World Evidence
Acorn AI, a Medidata Company

Dr. Galaznik has over 10 years of experience in the life sciences industry, with previous roles in RWD, HEOR, Market Access and Commercial Analytics at Takeda Oncology and Pfizer. He received his AB in Biology from Harvard University, his MD from Weill Medical College of Cornell University, and his MBA in Healthcare Management from the Wharton School.

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