Model based strategies towards protein A resin lifetime optimization and supervision.

Autor: Feidl F; Institute for Chemical and Bioengineering, ETH Zurich, Zurich, Switzerland., Luna MF; Institute for Chemical and Bioengineering, ETH Zurich, Zurich, Switzerland., Podobnik M; Institute for Chemical and Bioengineering, ETH Zurich, Zurich, Switzerland., Vogg S; Institute for Chemical and Bioengineering, ETH Zurich, Zurich, Switzerland., Angelo J; Biologics Process Development, Bristol-Myers Squibb, Devens, MA, USA., Potter K; Biologics Process Development, Bristol-Myers Squibb, Devens, MA, USA., Wiggin E; Biologics Process Development, Bristol-Myers Squibb, Devens, MA, USA., Xu X; Biologics Process Development, Bristol-Myers Squibb, Devens, MA, USA., Ghose S; Biologics Process Development, Bristol-Myers Squibb, Devens, MA, USA., Li ZJ; Biologics Process Development, Bristol-Myers Squibb, Devens, MA, USA., Morbidelli M; Dipartimento di Chimica, Ingegneria Chimica e Materiali, Politecnico di Milano, Milano, Italy., Butté A; DataHow AG, Zurich, Switzerland. Electronic address: a.butte@datahow.ch.
Jazyk: angličtina
Zdroj: Journal of chromatography. A [J Chromatogr A] 2020 Aug 16; Vol. 1625, pp. 461261. Date of Electronic Publication: 2020 May 25.
DOI: 10.1016/j.chroma.2020.461261
Abstrakt: The high cost of protein A resins drives the biopharmaceutical industry to maximize its lifetime, which is limited by several processes, usually referred to as resin aging. In this work, two model based strategies are presented, aiming to control and improve the resin lifetime. The first approach, purely statistical, enables qualitative monitoring of the column state and prediction of column performance indicators (e.g. yield, purity and dynamic binding capacity) from chromatographic on-line data (e.g. UV signal). The second one, referred to as hybrid modeling, is based on a lumped kinetic model, which includes two aging parameters fitted on several resin cycling experimental campaigns with varying cleaning procedures (CP). The first aging parameter accounts for binding capacity deterioration (caused by ligand degradation, leaching, and pore occlusion), while the second accounts for a decreased mass transfer rate (mainly caused by fouling). The hybrid model provides important insights into the prevailing aging mechanism as a function of the different CPs. In addition, it can be applied to model based CP optimization and yield forecasting with the capability of state estimation corrections based on on-line process information. Both approaches show promising results, which could help to significantly extend the resin lifetime. This comes along with increased understanding, reduced experimental effort, decreased cost of goods, and improved process robustness.
Competing Interests: Declaration of Competing Interest None.
(Copyright © 2020. Published by Elsevier B.V.)
Databáze: MEDLINE
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