Improving Automated Evaluation Methods For Stem Cell Production and Culture
Monday, December 3, 2018
Harvey Morse Auditorium
Presenter: Jeffery Bylund, Ph.D., Applications Manager, Stem Cell & Regenerative Medicine, Nikon Instruments Inc., USA
Routine microscopic observation of live cells is an essential part of cell quality assurance. However, manual observation is labor intensive and generally less objective, quantitative, precise, and consistent. It is also impossible to gain rich multi-parameter morphological and kinetic data from millions of individual cells in the culture dish by manual methods.
Using high-end optics and next-generation machine learning algorithms to acquire and analyze images of cells, the latest technology for cell observation enables visualization and quantification of an array of characteristics from any cell type in culture. This includes,
- Label-free, non-invasive cell counting by image analysis
- Accurate quantification of cell coverage area (i.e. for determining sub-culture confluence)
- Reproducible cell QC by replacing routine human observation with automated image analysis
- Create cell density distribution map
- Generating cell health metrics based on label-free, real-time analysis
During this workshop we will cover the following practical points for maintaining high quality cultures:
- Determine the timing for cell passage, drug addition, etc.
- Building tools to predict the success of cell culture
- Early detection of unwanted cell types
- Consistently ensuring best practices in cell culture are carried out