Mechanistic models are based on the laws of mathematics, physics, and physical chemistry, and combine all the elementary information of the system dynamics. Due to this fact, the model parameters have an actual physical meaning, which provides fundamental benefits for the scientific interpretation and understanding of the results. The model equations thereby present a clear distinct language, optimal for sharing growing process knowledge with a team.

Sharing and managing process knowledge

Integrated design of experiments (DoE) is a common approach to reduce the experimental load, while increasing the amount of information. The key idea is to plan an experimental series, such that the most information is gained from the minimum number of experiments. However, real experiments take up time and and are costly.

Downstream process simulation using GoSilico™ Chromatography Modeling Software replaces these lab experiments with computer simulations, achieving the same results within seconds at the price of computing power only. In comparison to the traditional one-factor-at-a-time approach, the level of process knowledge increases quickly with few experiments. After several hundreds of simulated experiments, the maximum level is reached and no more additional information is generated by adding more experiments. At the current time, the required level for regulatory acceptance is however reached with a few hundred experiments, quicker and cheaper than the fully experimental approach using one-factor-at-a-time.

Typically, a first draft process is created in the early development phase. This process is then refined throughout the development life cycle. Using a model based approach, e.g., in the GoSilico™ Chromatography Modeling Software, it is easy to manage and share this growing process knowledge within a team. As the actual process evolves, so does the model as more and more information is available to it. Process improvement is clearly documented in terms of the model equations and parameters, both saved in the form of a project file within the GoSilico™ Chromatography Modeling Software.


Generate a mechanistic process understanding and share process models with the team.


Model evolution during development life cycle from early to late stage downstream processing.


Maximize company knowledge and fulfil regulatory demands on Quality by Design (QbD) using GoSilico™ Chromatography Modeling Software.

Learn more about GoSilico™ Chromatography Modeling Software