Chromatographic parameter determination for complex biological feedstocks

Silvia M. Pirrung, Diogo Parruca da Cruz, Alexander T. Hanke, Carmen Berends, Ruud F.W.C. Van Beckhoven, Michel H.M. Eppink, Marcel Ottens*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)
46 Downloads (Pure)


The application of mechanistic models for chromatography requires accurate model parameters. Especially for complex feedstocks such as a clarified cell harvest, this can still be an obstacle limiting the use of mechanistic models. Another commonly encountered obstacle is a limited amount of sample material and time to determine all needed parameters. Therefore, this study aimed at implementing an approach on a robotic liquid handling system that starts directly with a complex feedstock containing a monoclonal antibody. The approach was tested by comparing independent experimental data sets with predictions generated by the mechanistic model using all parameters determined in this study. An excellent agreement between prediction and experimental data was found verifying the approach. Thus, it can be concluded that RoboColumns with a bed volume of 200 μL can well be used to determine isotherm parameters for predictions of larger scale columns. Overall, this approach offers a new way to determine crucial model input parameters for mechanistic modelling of chromatography for complex biological feedstocks.

Original languageEnglish
Pages (from-to)1006-1018
JournalBiotechnology Progress
Issue number4
Publication statusPublished - 2018


  • chromatography
  • downstream processing (DSP)
  • high-throughput process development (HTPD)
  • mechanistic modeling


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