FIRST BROADCAST:
Date: January 15, 2025
Time: 9:00am PT, 12:00pm ET, 6:00pm CET (EMEA)
SECOND BROADCAST:
Date: January 16, 2025
Time: 10:30 IST, 13:00 SGT/GC, 14:00 JST (APAC)
Rapid developments in gene-modified cell therapies, especially CAR T-cell therapies, has increased demand for fast and reliable analytics methods for research, in-process development, and manufacturing workflows. Characterizing cellular properties responsible for inherent donor variability in cell expansion, functionality, and post-editing efficacy has become increasingly important in the race to create robust, shorter, and less resource- and cost-intensive cell therapy workflows. These insights allow researchers to screen starting donor material and provide them with tools to help make informed decisions about the manufacturing process before it begins.
In this webinar, we demonstrate a use case for characterizing the health of starting donor material in cell therapy manufacturing using the Invitrogen™ Attune™ CytPix™ Flow Cytometer to monitor T-cell morphological metrics during ex vivo expansion and build a predictive model to forecast unmodified T-cell expansion across various donors, highlighting its potential to enable smart, donor-dependent manufacturing. In generating quantitative morphological data, we can derive valuable insights from cellular characteristics beyond traditional flow cytometric measurements.
Learning Objectives
- The role of image-enhanced flow cytometry and machine learning in enabling data-driven cell characterization and quality control throughout the cell therapy manufacturing workflow
- Techniques for enhancing population purity and cell viability assessments for research purposes
- The impact of image-based gating decisions on helping to reduce user-to-user variability and improving standardization in cell therapy processes
Webinars will be available for unlimited on-demand viewing after live event.