Hamburger. With a Side of Computational Modeling

Publish Date

13 AUG 2020


Producing the hamburger of the future will require use of advanced techniques. In this post, we explore how computational modeling, in combination with some decades-old research, can help the cultivated meat industry take a major step forward – and reveal first insights from a proof of concept.

“Computational modeling” is the use of computers to simulate and study complex systems using mathematics, physics and computer science. So...what could computational modeling possibly have to do with cultivated meat? Quite a bit! Meat that is “grown” in the laboratory is expected to help feed our growing population and reduce the ecological impact and resources needed to raise livestock. An essential step in producing cultivated meat is the growth of cells in large quantities, often attached to tiny beads called microcarriers, in bioreactors. 


It may sound simple but in fact, it’s quite complicated! Large-scale, efficient production of “biomass” is going to require a significant leap forward in current processes and technology. The Cultivated Meat Modelling Consortium (CMMC), of which Merck KGaA, Darmstadt, Germany is a founding partner, is leading the way. The CMMC, in close collaboration with the Cultured Meat Innovation Field team at our Silicon Valley Innovation Hub, has identified a number of workstreams where computational modelling can help advance the industry. Combined with traditional lab research, computational modeling can provide a new dimension of insights to researchers and significantly accelerate cultivated meat R&D and the time to market. In other industries with comparable design challenges, computer simulations have been used to reduce costs, save time and drive innovation. Before computer simulations can be applied to cultivated meat, however, new and effective modeling methodologies are needed.

Simulating the Bioreactor

As a first step, the CMMC kicked off a proof-of-concept (POC) in February 2020. With the POC, sponsored by our Silicon Valley Innovation Hub, the team sought to simulate a stirred tank bioreactor, a tool used by cultivated meat companies to generate biomass, as this offers strong potential to accelerate the industry as a whole. These bioreactors come in many sizes and can have diverse geometries, configurations and system control technologies, as well as different biological, biophysical and fluid flow characteristics.

To understand the impact of some of these variables on cell growth, the POC team applied two modelling approaches – agent-based modelling (ABM) and computational fluid dynamics (CFD) – to stirred tank reactors used to grow cells adhered to microcarriers. 

ABM was used to model the biological processes and interactions that determine cell behavior. In simplified terms, ABM helps make sense of how the behaviors of numerous individual, autonomous “agents” work in relationship to create an emergent, whole-system outcome, similar to how stationary waves of freeway congestion emerge from the behavior of individual “agent” drivers. By modelling each cell or microcarrier as an agent individually, its direct contribution to biomass production can be understood. CFD was used to model the fluid flow and forces that are created when fluids and microcarriers are stirred in the bioreactor. Perhaps some of you vaguely remember something about fluid dynamics from physics class!  

Revealing new Insights

Along with these advanced techniques, the POC team turned to a 1987 research paper (1) which provided an analysis of hydrodynamic effects on microcarrier cultures. By reconstructing the simple bioreactor geometry and microcarrier-bound cells described in the paper in computer simulations, the POC team set out to show the promise of the modeling approach by recapitulating a trend that neither ABM nor CFD could achieve alone. Namely, that at a higher rotor speed in the bioreactor, biomass production dropped, and that there was a change in production rate as microcarriers saturate with cells. 

After three months of development, the POC team built a model that was able to predict a decrease in biomass production at a higher stir rate, signifying a leap forward in the application of modeling to bioreactor research and design. As a foundational tool, the model represents a platform from which many disparate streams of inquiry can now be investigated.

The next phase of the POC involves engaging additional industry stakeholders to identify and further develop those streams which have the greatest potential to accelerate the whole industry. 

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(1) Croughan, M.S., Hamel, J.F., and Wang, D.I. (1987). Hydrodynamic effects on animal cells grown in microcarrier cultures. Biotechnol Bioeng 29, 130-141.