Mechanistic modeling completely replaces experiments: Myth or Fact?
Myth…for now
A mechanistic model relies on first principles based on physico-chemical phenomena and requires estimating a number of model parameters specific to the case under investigation.
The evaluation of model parameters is typically done based on a set of well targeted experiments.
While we’re not yet able to get quantitative reliable predictions of chromatographic processes without performing any experiment to estimate model parameters, in some relatively simple cases such as predicting aggregate removal by size exclusion, prior knowledge can be used to run completely digital simulations to identify rough qualitative trends.
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 can help secure scale-up: 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?
