Optimising bioreactor processes with in-situ product removal using mathematical programming: a case study for propionate production

Designing and operating bioreactors with in-situ product removal (ISPR) can be challenging, particularly in discontinuous systems, where the ISPR and substrate feeding need to be effectively scheduled. Mathematical models can help assess different scheduling regimes in the fermentation medium and provide a means to optimise the process. Focusing on a propionate production case study, a model of a co-culture batch fermentation with electrodialysis (the ISPR system), was developed. Using this model, the product yield and/or the productivity were maximised by 1) single objective optimisation maximising the product yield (0.49 gpropionate /gglucose) or productivity (0.75 gpropionate/L/h), 2) multi objective optimisation to pursue trade-off solutions between the yield and productivity and 3) a stochastic optimisation maximising the productivity robustly (0.64 gpropionate/L/h) to account for uncertainties associated to the model parameters. With this contribution it is demonstrated that, through mathematical models, ISPR can be implemented and adapted to the user's objectives.

Subjects

Biotechnology

Design under uncertainty

Downstream processing

Kinetic modelling

Operational design

Product inhibition

DDC Class

570: Biowissenschaften, Biologie

600: Technik

Publication version

publishedVersion

Lizenz

https://creativecommons.org/licenses/by-nc-nd/4.0/

Name

1-s2.0-S009813542200391X-main.pdf

Size

3.98 MB

Format

Adobe PDF

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Optimising bioreactor processes with in-situ product removal using mathematical programming: a case study for propionate production