Details

Autor(en) / Beteiligte

• Liu, Songsong
• Simaria, Ana S.
• Farid, Suzanne S.
• Papageorgiou, Lazaros G.

Titel

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

Ist Teil von

• Computers & chemical engineering, 2014-09, Vol.68, p.151-164

Ort / Verlag

Kidlington: Elsevier Ltd

Erscheinungsjahr

2014

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• •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.