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Parameter-by-parameter estimation method for adsorption isotherm in hydrophobic interaction chromatography.

Yu-Xiang Yang1, Yu-Cheng Chen1, Shan-Jing Yao1

  • 1Key Laboratory of Biomass Chemical Engineering of Ministry of Education, Zhejiang Key Laboratory of Smart Biomaterials, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou 310058, China.

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|January 14, 2024
PubMed
Summary

A new parameter-by-parameter (PbP) method simplifies hydrophobic interaction chromatography (HIC) model parameter estimation. This approach accelerates biopharmaceutical process development by systematically determining HIC parameters, reducing complexity.

Keywords:
Hydrophobic interaction chromatographyMechanistic modelMollerup isothermParameter estimation

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Area of Science:

  • Biotechnology
  • Chemical Engineering
  • Chromatography

Background:

  • Hydrophobic interaction chromatography (HIC) is crucial for biopharmaceutical purification.
  • Current HIC process development is time-consuming, with inefficient model parameter estimation.
  • Mechanical models offer potential for process characterization and design.

Purpose of the Study:

  • To develop an efficient and logical parameter estimation strategy for HIC mechanical models.
  • To propose a parameter-by-parameter (PbP) method for estimating Mollerup isotherm parameters.
  • To reduce the complexity and time required for HIC process development.

Main Methods:

  • A novel parameter-by-parameter (PbP) method was developed based on theoretical derivation and simplifying assumptions.
  • The PbP method involves three steps: linear regression (LR), linear approximation (LA), and inverse method.
  • LR estimates salt-protein interaction and equilibrium constant; LA estimates stoichiometric parameter and maximum binding capacity; inverse method estimates protein-protein interaction and kinetic coefficient.

Main Results:

  • The PbP method systematically estimates HIC parameters individually, reducing the number of parameters for inverse estimation from six to two.
  • The study identified optimal conditions for LR (dilution) and LA (transition/nonlinear regions).
  • The PbP-HIC method was validated through numerical experiments and real-world applications, enhancing mechanistic understanding.

Conclusions:

  • The PbP method provides a systematic and efficient strategy for estimating HIC model parameters.
  • This approach accelerates HIC process development and improves mechanistic understanding.
  • The PbP method shows potential for application to other models derived from stoichiometric displacement principles.