Ozempic Maker Pumps $7.6M in AI Project to Make Non-UPF Plant-Based Meat
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Running over the next seven years, the AI4NaturalFood project is backed by a 50 million kroner ($7.6M) grant from the Novo Nordisk Foundation, which owns the eponymous pharmaceutical giant famous for diabetes and obesity medications like NovoRapid, Ozempic, and Wegovy.
As meat alternatives continue to be scrutinised for their level of processing, a new University of Copenhagen project aims to tackle this with food science and artificial intelligence (AI).
Running over the next seven years, the AI4NaturalFood project is backed by a 50 million kroner ($7.6M) grant from the Novo Nordisk Foundation, which owns the eponymous pharmaceutical giant famous for diabetes and obesity medications like NovoRapid, Ozempic, and Wegovy.
The investment is part of the company’s Recruit grant, which aims to help Danish universities attract top researchers and build strong ecosystems within certain areas of support.
It comes weeks after Novo Nordisk came under heavy criticism by nutrition researchers for another project, which aims to create the “next generation” of the Nova classification, the tiered system that groups foods by the amount of processing.
Mild processing is more complex – AI can help simplify it
The AI4NaturalFood project is being helmed by Remko Boom, who spent 26 years studying plant-based foods at Wageningen University & Research, and is starting a new research group at the university’s food science department, called Food Materials Engineering.
He will work with data scientists from the university to develop new experimentation processes that generate sufficient data and create AI models to interpret the information.
“Food is fundamentally very complex. A piece of bread contains hundreds of different substances interacting with each other: there’s a molecular structure, a colloidal structure, a microscale structure, [a] macroscale structure – there’s structure everywhere. And this structure largely determines the properties,” he explained.
“In food science, we traditionally tried to reduce these complexities, to make it possible to understand what is happening. I think that now is the time that we, as food scientists, should not shy away from the complexity, but instead aim for it. With the availability of AI, we can begin to capture all these interactions and use them rather than trying to avoid them.”
Boom argued that mild processing retains more of the plant’s natural structure and composition, which makes it more complex to work with. This is where AI comes in. “Rather than the elaborate and costly process of breaking down raw materials and then rebuilding a product from the resulting refined ingredients, we’re going to use much simpler methods to create enriched fractions and then use AI to predict how we can combine them into good foods,” he said.
“It could perhaps ultimately predict how food products will turn out before even starting the production process. In the future, it could even help us determine which crops are best suited for specific food applications.”
With these “simpler” methods, he noted that proteins sourced from legumes, seeds and other plants would be able to retain more of the original structure and nutrients from the raw materials. “We have already proven the principle and got some very nice products from it. And most importantly, we can do it with a lot less energy and water use,” he said.