Mechanistic modeling can help secure scale-up: Myth or Fact?
Fact
Unlike statistical models which are based on correlations and are only valid for their calibration data set, mechanistic model parameters have an actual physical meaning and can be applied to different process setups and process scales.
This gives you confidence in scaling up your chromatography processes by changing column dimensions and even enables you to adapt the operating sequence if needed. Mechanistic modeling can also help with troubleshooting. If the scaled-up process isn’t performing as expected, you can test potential reasons via simulation and take appropriate action based on the results.
Do you want to learn more about mechanistic chromatography modeling ? Download our infography below.
Curious about more myths and facts in the world of mechanistic modeling? Each post in our series tackles common misconceptions and provides insightful answers to frequently asked questions. Check out the other posts in this series:
- Mechanistic modeling completely replaces experiments: Myth or Fact?
- Mechanistic modeling is complex: Myth or Fact?
- Mechanistic modeling requires many experiments: Myth or Fact?
- Mechanistic modeling can help switch from batch to continuous: Myth or Fact?
Ypso-Facto is a service company helping industrial firms to develop, optimize and secure their chemical processes and bioprocesses.