Webinar
Presented on: May 18, 2026
This webinar, the fourth in the MRCT Center’s AI Digital Twins and Synthetic Data series, focused on data provenance and quality, model validation, and the emerging infrastructure needed to support the clinical and regulatory adoption of these technologies. Panelists explored how to evaluate whether the models used are credible, whether the data underlying them are reliable and traceable, and whether the outputs can be verified and validated for use in regulatory and clinical decision-making. They also discussed what it means for a model to be “fit for purpose,” how definitional differences among these technologies shape regulatory review, and how clinicians, sponsors, reviewers, and regulators may use, interpret, and deploy these tools.
Panelists: Daniele Bertolini, Principal Machine Learning Scientist, Unlearn.AI | Tina Morrison, VP, Scientific Strategy, EQTY Lab | Chao-Yi Wu, Assistant Professor of Neurology, Massachusetts General Hospital
Moderator: Barbara Bierer, Faculty Director, MRCT Center