A leading biotech company was facing challenges with their flow cytometry workflows due to inefficient, manual processes that were time consuming, high effort and error prone.
This case study shows how this biotech organization was able to automate, simplify, and improve the quality of their flow cytometry workflows by addressing the pain points that include:
- Manual data manipulation
- High utilization of instruments
- Slow, complex, and risky data preparation processes
Read this full case study to learn about how to improve and accelerate flow cytometry workflows with the Tetra Scientific Data and AI Cloud™.
