Predictive Pooling Strategy: Global Biotech Company Reduces Risk in Downstream Purification
In high-cost biotechnology applications, keeping processes as efficient as possible is a necessity. Fortunately, historical data and analytics tools are constantly providing new opportunities for optimization.

In this case study, a biotechnology site needed to improve the yield of their downstream processes. They produced a rare disease medicine with a value of hundreds of thousands of dollars per gram, meaning process optimization was vital. Though they had access to a wealth of historical data, they were forced to manually gather and correlate data, slowing the process and creating potential for human error.

With Aizon, the biotech site bypassed manual correlation, leading to:

  • 93% reduction in time spent setting up pooling
  • Manual data gathering went from a day-long task to mere minutes
  • Higher accuracy and higher confidence in pooling strategies
  • Ability to simulate outcomes, reserving resources

Download Case Study

©2021 Aizon. All rights reserved.
Privacy Policy    Legal Disclaimer    Cookies Policy