Straightforward method for calibration of mechanistic cation exchange chromatography models for industrial applications

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  • David Saleh
    Late Stage DSP Development Boehringer Ingelheim Pharma GmbH & Co. KG Biberach Germany
  • Gang Wang
    Late Stage DSP Development Boehringer Ingelheim Pharma GmbH & Co. KG Biberach Germany
  • Benedict Müller
    Late Stage DSP Development Boehringer Ingelheim Pharma GmbH & Co. KG Biberach Germany
  • Federico Rischawy
    Late Stage DSP Development Boehringer Ingelheim Pharma GmbH & Co. KG Biberach Germany
  • Simon Kluters
    Late Stage DSP Development Boehringer Ingelheim Pharma GmbH & Co. KG Biberach Germany
  • Joey Studts
    Late Stage DSP Development Boehringer Ingelheim Pharma GmbH & Co. KG Biberach Germany
  • Jürgen Hubbuch
    Institute of Engineering in Life Sciences, Section IV: Biomolecular Separation Engineering, Karlsruhe Institute of Technology (KIT) Karlsruhe Germany

書誌事項

公開日
2020-03-04
権利情報
  • http://onlinelibrary.wiley.com/termsAndConditions#vor
DOI
  • 10.1002/btpr.2984
公開者
Wiley

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説明

<jats:title>Abstract</jats:title> <jats:p>Mechanistic modeling of chromatography processes is one of the most promising techniques for the digitalization of biopharmaceutical process development. Possible applications of chromatography models range from in silico process optimization in early phase development to in silico root cause investigation during manufacturing. Nonetheless, the cumbersome and complex model calibration still decelerates the implementation of mechanistic modeling in industry. Therefore, the industry demands model calibration strategies that ensure adequate model certainty in a limited amount of time. This study introduces a directed and straightforward approach for the calibration of pH‐dependent, multicomponent steric mass action (SMA) isotherm models for industrial applications. In the case investigated, the method was applied to a monoclonal antibody (mAb) polishing step including four protein species. The developed strategy combined well‐established theories of preparative chromatography (e.g. Yamamoto method) and allowed a systematic reduction of unknown model parameters to 7 from initially 32. Model uncertainty was reduced by designing two representative calibration experiments for the inverse estimation of remaining model parameters. Dedicated experiments with aggregate‐enriched load material led to a significant reduction of model uncertainty for the estimates of this low‐concentrated product‐related impurity. The model was validated beyond the operating ranges of the final unit operation, enabling its application to late‐stage downstream process development. With the proposed model calibration strategy, a systematic experimental design is provided, calibration effort is strongly reduced, and local minima are avoided.</jats:p>

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