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Rapid identification of Goldilocks CAR T cells using z-Movi® Cell Avidity Analyzer
While great clinical successes have been achieved using CD19-specific CAR T cells, still adoptive cell therapy does not always work efficiently, or leads to unwanted cytotoxicity as a result of cytokine storms or on-target/off-tumor effects. Interestingly, over the last couple of years it has become apparent that affinity-tuned CAR T cells display enhanced expansion and prolonged persistence in patients, and that this strategy also resulted in discrimination between tumor cells and normal cells, sparing the latter one.

Although affinity screening and surface plasmon resonance measurements for binding kinetics will lead to the identification of a range of affinity-tuned CARs, it will not assist in choosing the optimal candidate. For this reason, a series of standard in vitro assays need to be performed that often requires long-term co-cultures or the use of radioactive isotopes. Besides these drawbacks, such assays do not always accurately predict the most potent candidate(s) for further development in clinical use. In this webinar we demonstrate that measuring cellular avidity, i.e. overall binding strength between effector and target cell, using z-Movi® Cell Avidity Analyzer could aid in quickly identifying optimal functioning CARs.

z-Movi is a novel and unique instrument for accurate and direct measurement of cell–cell interaction strength using acoustic forces. This new technology provides you with predictive, reproducible, and fast high-throughput results at a single-cell level. We will deep-dive into the basic principle of the z-Movi, the workflow and intuitive software package will assist in getting precise cell avidity information of hundreds of cells simultaneously. Finally, we will demonstrate the great potential of the z-Movi for accelerating the development of CAR-based immunotherapy against cancer.

Speaker: Rogier Reijmers, PhD
Principal Scientist, Immuno-Oncology Department, LUMICKS
Cost: Free of charge
Duration: 45 minutes
Language: English
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