An MIQP framework for metabolic pathways optimisation and dynamic flux analysis

Gerken-Starepravo, Lucas; Xian-feng, Zhu; Cho, Bovinille Anye; Vega-Ramon, Fernando; Pennington, Oliver; Rio‐Chanona, Ehecatl Antonio del; Jing, Keju; Zhang, Dongda

doi:10.1016/j.dche.2022.100011

Cited by 6 publications

(2 citation statements)

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“…This method has been validated by simulating glycolytic reaction fluxes in Escherichia coli and human red blood cells [ 113 ]. Starepravo et al proposed a hybrid model that integrated the kinetic model and dynamic MFA to simulate the flux change in the batch fermentation process with the combination of a single-level mixed-integer quadratic program (MIQP) [ 114 ]. This model can identify the shortest metabolic pathway from substrate to product, which has been applied in the biosynthetic pathway for astaxanthin production in Saccharomyces cerevisiae , reducing the original metabolic network by 70% [ 114 ].…”

Section: Applications Of Hybrid Models In Bioprocess Developmentmentioning

confidence: 99%

“…Starepravo et al proposed a hybrid model that integrated the kinetic model and dynamic MFA to simulate the flux change in the batch fermentation process with the combination of a single-level mixed-integer quadratic program (MIQP) [ 114 ]. This model can identify the shortest metabolic pathway from substrate to product, which has been applied in the biosynthetic pathway for astaxanthin production in Saccharomyces cerevisiae , reducing the original metabolic network by 70% [ 114 ]. Carinhas et al updated a stoichiometric model to identify the key metabolic pathways involved in baculovirus production in insect cells by partial least squares (PLS) and MFA [ 115 ].…”

Section: Applications Of Hybrid Models In Bioprocess Developmentmentioning

confidence: 99%

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From Spatial-Temporal Multiscale Modeling to Application: Bridging the Valley of Death in Industrial Biotechnology

et al. 2023

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The Valley of Death confronts industrial biotechnology with a significant challenge to the commercialization of products. Fortunately, with the integration of computation, automation and artificial intelligence (AI) technology, the industrial biotechnology accelerates to cross the Valley of Death. The Fourth Industrial Revolution (Industry 4.0) has spurred advanced development of intelligent biomanufacturing, which has evolved the industrial structures in line with the worldwide trend. To achieve this, intelligent biomanufacturing can be structured into three main parts that comprise digitalization, modeling and intellectualization, with modeling forming a crucial link between the other two components. This paper provides an overview of mechanistic models, data-driven models and their applications in bioprocess development. We provide a detailed elaboration of the hybrid model and its applications in bioprocess engineering, including strain design, process control and optimization, as well as bioreactor scale-up. Finally, the challenges and opportunities of biomanufacturing towards Industry 4.0 are also discussed.

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Section: Applications Of Hybrid Models In Bioprocess Developmentmentioning

confidence: 99%

Section: Applications Of Hybrid Models In Bioprocess Developmentmentioning

confidence: 99%

From Spatial-Temporal Multiscale Modeling to Application: Bridging the Valley of Death in Industrial Biotechnology

et al. 2023

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Towards industrial biological hydrogen production: a review

Teke,

Anye Cho,

Bosman

et al. 2023

World J Microbiol Biotechnol

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Increased production of renewable energy sources is becoming increasingly needed. Amidst other strategies, one promising technology that could help achieve this goal is biological hydrogen production. This technology uses micro-organisms to convert organic matter into hydrogen gas, a clean and versatile fuel that can be used in a wide range of applications. While biohydrogen production is in its early stages, several challenges must be addressed for biological hydrogen production to become a viable commercial solution. From an experimental perspective, the need to improve the efficiency of hydrogen production, the optimization strategy of the microbial consortia, and the reduction in costs associated with the process is still required. From a scale-up perspective, novel strategies (such as modelling and experimental validation) need to be discussed to facilitate this hydrogen production process. Hence, this review considers hydrogen production, not within the framework of a particular production method or technique, but rather outlines the work (bioreactor modes and configurations, modelling, and techno-economic and life cycle assessment) that has been done in the field as a whole. This type of analysis allows for the abstraction of the biohydrogen production technology industrially, giving insights into novel applications, cross-pollination of separate lines of inquiry, and giving a reference point for researchers and industrial developers in the field of biohydrogen production.

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