385 Likes Capturing real-world data and evidence in clinical trials Posted by Emily Lewis, Digital Care Transformation Neurology 20-Jul-2022 At UCB, we see the many benefits of integrating technology in all aspects of our business to amplify the power of scientific innovation and to improve patient care. In the second UCB Digital Health Roundtable (June 2022) an expert panel discussed how clinical research, and the data we use within it, can be more reflective of the real-world settings in which patients live, so that providers can better close gaps in care and improve patient outcomes. The expert speaker panel included: Ying Lu, PhD (Professor of Biomedical Data Science, Stanford University), Jeremy Rassen, Sc.D (Co-Founder and President, Aetion, Inc.), Dorothee Bartels, PhD (Global Head of RWE and Digital Sciences, UCB), Devin Gilliam, Head of Clinical Trials (Datavant). For decades the best practices of clinical research involved rigidly designed, prospective randomized controlled trials (RCTs). While that remains the case in many scenarios, these kinds of trials collected data under ideal conditions and did not always reflect the routine clinical practice settings they are meant to inform. Over the last decade, as real-world data methodology advances and related regulatory guidance has matured it has allowed us to generate the evidence needed for strategy and decision making within development itself. The expert panel discuss the need to further develop a common language, standards, structure and process, and global best practices around these new evidence generation frameworks to meet this rapidly advancing world. Watch the roundtable to find out more: https://youtu.be/tYfym1U1vD4. Leave a Comment You must have JavaScript enabled to use this form. Please enter your name Please enter your email address By submitting your personal data, you agree with UCB's Data Privacy Policy. Furthermore, for more information on the terms of use of this website please visit our Legal Notice, accessible here. CAPTCHA Get new captcha! What code is in the image? Enter the characters shown in the image. Leave this field blank