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  • February 05, 2024

Predicting the impact of buffer type and pH : Application to protein purification by IEX

 Challenge The challenge was inspired by the experimental data reported in Pabst et al. J. Chrom. A (2008) 1181, 83-94. A poor separation between two proteins, Serum Albumin (SA) and Serum Transferrin (ST), was observed (Fig. 1). The separation was performed on a weak cation exchange...

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  • January 19, 2024

Mechanistic modeling can help switch from batch to continuous: Myth or Fact?

Fact Once model parameters have been determined with a single column system , they can be used to perform simulations of multicolumn chromatography (MCC) with any number of columns. Calculating key performance indicators (KPIs) for both single and multicolumn systems can help to compare options...

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  • January 09, 2024

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...

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  • December 18, 2023

Reduced experimental work by 4 compared to DoE for an oligonucleotide ion exchange process

" GSK Engaged Ypso-Facto’s expertise, their Ypso-Ionic software and GPX approach to develop a mechanistic model of a complex ion-exchange purification process.    Compared with the classical statistical DoE approach, only 25% of the experimental work was required, but we also achieved...

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  • December 13, 2023

Mechanistic modeling is complex: Myth or Fact?

Myth The underlying equations that represent physical phenomena are necessarily complex, but using mechanistic models to gain process understanding doesn’t have to be. You don’t need to be a computerprogrammer or simulation expert with years of experience. With a clear methodology, a well- designed...

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  • December 06, 2023

Mechanistic modeling requires many experiments: Myth or Fact?

Myth A customer told us recently that  mechanistic modeling required only 25% of the experimental work required for a classical statistical DoE approach  and they also achieved much more, including  deep process understanding. The number of experiments required depends on the objectives such...

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  • November 28, 2023

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...

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  • October 26, 2023

Doubled productivity of a multi-column ion exchange chromatographic process with increased purity

About the optimization of a multi-column Ion Exchange system :   « In combination with AKBM “user-knowledge” and intuition, Ypso-Facto used experimental laboratory- and production-data and made simulation-models with the software “Ypso-Ionic”. With this GPX approach, Ypso-Facto...

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  • October 25, 2023

Three Benefits of Mechanistic Modeling For Chromatographic Process Development

Optimizing chromatographic processes can be achieved by employing mechanistic modeling, with the following benefits: Increase Process Understanding Get to the core of chromatography with mechanistic modeling. The combination of well targeted experiments with mechanistic simulations...

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