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

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

doi:10.1016/j.compchemeng.2014.05.005

Songsong Liu, Ana S Simaria + Show 2 more

Open Access

https://doi.org/10.1016/j.compchemeng.2014.05.005

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Abstract

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.

Highlights

The biopharmaceutical industry has been a rapidly growing sector during the past decade
We present the mixed integer linear fractional programming (MILFP) model based on the proposed mixed integer nonlinear programming (MINLP) model using exact linearisation techniques (Floudas, 1995; Harjunkoski et al, 1998; Sherali and Adams, 1999)
We investigated the computational performance of the Dinkelbach algorithm for the proposed MILFP model

Summary

Introduction

The biopharmaceutical industry has been a rapidly growing sector during the past decade. A key decision for mAb purification is the selection of the chromatography sequence. There usually exist multiple chromatography steps in the mAb purification process, and each step has a number of suitable candidate resins/types for selection. An importation issue is how to choose the best combination of resins/types for all chromatography steps to be of most benefit to the whole downstream process. At each chromatography step, another key decision is the column sizing strategy, e.g. opting to run a smaller column for several cycles so as to reduce resin costs or a large column for fewer cycles so as to save time and labour costs. Decisions on the chromatography column sizes include the selection, the bed height and diameter of each column and the number of cycles to run and the number of columns to use in parallel

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