Senior Scientist Takeda Development Center Americas, Inc. Cambridge, Massachusetts
This presentation introduces Time-Lapse Flow™ Cytometry, a novel single-cell technology that enables dynamic, real-time tracking of immune cell activation. By capturing kinetic phenotypes of T-cell responses, this approach provides mechanistic insights that conventional flow cytometry often misses. Leveraging these high-resolution datasets, machine learning models can predict immunogenicity with improved accuracy, supporting early risk assessment and enhancing translational decision-making in drug development.
Learning Objectives:
Understand the importance of immunogenicity in drug development.
Explore current in vitro immunogenicity screening strategies.
Discover Time-Lapse Flow™ Cytometry, an innovative single-cell technology that enables dynamic, real-time tracking for advanced immunogenicity assessment.
Learn how machine learning models trained on single-cell data can improve the accuracy of immunogenicity prediction.
