Optimising chromatography strategies of antibody purification processes by mixed integer fractional programming techniques

•Optimal chromatography sequencing and column sizing strategies are addressed.•An MINLP model is proposed, which then is reformulated as an MILFP model.•Dinkelbach algorithm is adapted as a solution approach for the MILFP model.•Application on an example shows the applicability of the models and app...

Full description

Saved in:
Bibliographic Details
Published in:Computers & chemical engineering 2014-09, Vol.68, p.151-164
Main Authors: Liu, Songsong, Simaria, Ana S., Farid, Suzanne S., Papageorgiou, Lazaros G.
Format: Article
Language:English
Subjects:
Analytical chemistry
Applied sciences
Biopharmaceutical manufacturing processes
Chemistry
Chromatographic methods and physical methods associated with chromatography
Chromatography
Chromatography purification
Decisions
Dinkelbach algorithm
Exact sciences and technology
mAb
Mathematical models
Mathematical programming
MILFP
MINLP
Mixed integer
Operational research and scientific management
Operational research. Management science
Programming
Sequencing
Sizing
Strategy
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:•Optimal chromatography sequencing and column sizing strategies are addressed.•An MINLP model is proposed, which then is reformulated as an MILFP model.•Dinkelbach algorithm is adapted as a solution approach for the MILFP model.•Application on an example shows the applicability of the models and approach. The strategies employed in chromatography steps play a key role in downstream processes for monoclonal antibody (mAb) manufacture. This work addresses the integrated optimisation of chromatography step sequencing and column sizing in mAb purification processes. Chromatography sequencing decisions include the resin selection at each typical step, while the column sizing decisions include the number of columns, the column diameter and bed height, and number of cycles per batch. A mixed integer nonlinear programming (MINLP) model was developed and then reformulated as a mixed integer linear fractional programming (MILFP) model. A literature approach, the Dinkelbach algorithm, was adopted as the solution method for the MILFP model. Finally, an industrially-relevant case study was investigated for the applicability of the proposed models and approaches.
ISSN:0098-1354
1873-4375
DOI:10.1016/j.compchemeng.2014.05.005