Why a plant protein scanning patent could potentially change the food industry
Towards the end of last year, JUST (formerly Hampton Creek) patented its revolutionary plant protein scanning process, but what impact can this have moving forward?
When the company formerly known as Hampton Creek rebranded as JUST, it did so with a purpose in mind. Over the next five years, JUST and its team of experts aims “to do everything they possibly can every single day to increase the probability that, before we die, a fair, honest and just food system is the food system in every community”.
Already, JUST is famed for its products like “clean meat”, alternative mayonnaise and cookie dough, and JUST Scramble, as well as its focus on sustainable ingredients.
In September last year, the company was issued with what is believed to be the first ever patent covering machine learning methods and systems for food ingredient discovery. JUST rightfully sees this as a major milestone in its mission and has incorporated automation, machine learning and AI to create what could prove to be a hugely disruptive technological breakthrough.#
The patent ‘discovery systems for identifying entities that have a target property’ took tens of millions of dollars and several years to complete onsite at the company’s 93,000 sq ft headquarters in San Francisco.
The system, nicknamed ‘Blackbird’, combines of one-of-a-kind robotics, proprietary plant databases, AI and predictive modeling. This essentially automates the system for researching plant proteins by breaking them down to the molecular level and searching for desirable properties — like emulsification, protein content and thermal stability. The new technology does this by bringing together all manner of expertise and specialisms.
“The platform is not only a game-changer for us because it helps JUST dramatically increase the probability of identifying discoveries for our products and our ability to bring healthier, diversified plant-based products to market, but it can also identify materials that help other food companies make their products better for consumers and the planet,” says Meng Xu, Director of Bioinformatics at JUST.
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CEO Josh Tetrick gives a good description of how exactly the whole operation works. "Try to imagine if we were flying around the world and I took you to Merck pharmaceutical company,” he explained to Food Dive. “And I looked at their screening platform, and I grabbed elements of the screening platform out, and you went to a large protein processor somewhere that's doing potato protein, and then we got some of their equipment.
“Then we went to Genentech into their analytical chemistry lab and I said, 'All right, let's bring that over here.' Then we went to a Michelin star restaurant — let's bring some of that equipment and some of those benches over here. Then we went to Nestlé and took some of the food scientists and the food scientists’ equipment and we put it in there. Then we went to the Carnegie Institute at Stanford, the home of some of our computational biologists that work for us. They look at all this data and find meaningful relationships in it."
That’s easy enough to claim, but how exactly is that the case? FDF World also spoke to JUST’s Director of Automation, Chingyao Yang. He works as a ‘translator’ for the JUST robots, working with biochemists, food scientists, data scientists and engineers amongst others.
“While our team has amazing talent working on manual experiments on proteins and food, my goal is to educate these robots with our team's knowledge since they are part of JUST family members,” he says.
“With the goal of making a major impact on how people think of food, we challenge ourselves to find solutions across different disciplines including hardware design, software integration, data analysis, etc. Combined with knowledge from our chefs, food chemists, and materials scientists, robots accelerate our discovery pipeline and explore more opportunities from different corners around the globe.”
But why is this particular technological innovation so important to that mission? “This technology speeds up the rate of discovery for new plant candidates for better, more sustainable food production. We first started analysing plant protein content by hand,” says Xu. “Now, we’re using our novel automated discovery platform – using robotics and machine learning – to explore their potential much faster. The more data we gather, the more we’ll discover proteins in plants that will improve the food system.
“We’re using data to increase the probability of discoveries to empower our own food production and to empower others in the industry to make better food that's healthier and more sustainable.”
In addition, the technology is especially exciting because it offers a functionality not seen before. “Our platform is integrated with novel ideas and enhanced performances of existing technology,” Yang continues. “We built these workflows from scratch, understanding deeply about food technology and protein biochemistry.
“Connecting dots from multiple perspectives, we deliver rich and interactive information that has not seen before in this industry. JUST proudly owns the advantages of the rate of discovery, precision, accuracy, and the capacity of new technologies. For example, we designed and collaborated with different instrument vendors to create unique robots that characterise the gelling and foaming properties of plant candidates. With in-house data systems and analysis, we dynamically search for candidates that provide functionalities in need.
“With the rich information from a collection of experiments, we started thinking about the multiple iterations of development holistically. Combined with in-house chefs, engineers, and scientists' experiences, the robots and data systems shorten turn-around time and provide us with an unprecedented perspective on how we utilise these plants in this industry.”
The team at JUST is always busy trying to find new ways to innovate and currently, amongst other projects, is working on protein biochemistry and food chemistry experiments as well as making enhancements on the existing systems. These include making different versions of buffer conditions for a high throughput screening process and developing more efficient methods to screen samples effectively on emulsion properties.
However, it’s the newly-patented platform the company is most excited about, and there is a quiet confidence that after causing a stir when it was announced, it can now go onto severely disrupt the space and even spark some further innovation.
“We are proud of be one of the first movers in this industry and at the forefront implementing this novel technology,” adds Xu. “With knowledge and experiences from different disciplines, we look forward to finding more integrations in this industry. We will continue to see the rise of AI, machine learning and robotic systems in food discovery and production.”