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Rapid advances in biotech and AI hold huge promise for future food security

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Muhammad Nakhooda is Associate Professor of Biotechnology at the Cape Peninsula University of Technology, Cape Town, South Africa.

With the help of artificial intelligence, the costs of cellular agriculture in terms of resources needed and time are rapidly reducing, which will translate to greater accessibility once it reaches the global market.

Unsustainable livestock farming and commercial fishing practices to sustain growing human populations and expanding appetites have contributed to runaway climate change, immense loss of biodiversity, decline in ocean catches and unprecedented pollution on land and in rivers and our oceans.

Thankfully, we have been exploring numerous technologies to mitigate risks and seek sustainable alternatives to reduce our impact on the planet while maintaining the lifestyles to which we’ve become accustomed.

In addition to plant-based meat alternatives, lab-grown meats (or cellular agriculture) represent a very viable option to meet at least some of our need for animal protein.

Cellular agriculture entails the production of meat, dairy or even eggs from once-living cells using culture technologies that mimic natural growth and development and harness the genetic predisposition for cells to grow, develop and proliferate. Scientists can control the composition of such products so that they contain less or more fat, elevated nutrients, and are pathogen-free.   

Since the first start-up companies in this space in 2011, and the first cultured beef patty was presented to the public in 2013, many more companies around the world, including some in South Africa – notably Mzansi Meats (now Newform Foods), Sea-Stematic and Mogale Meats – have been developing the technology and making significant gains along the way.

Lab-cultured abalone, for example, is a very real possibility, as is fish protein from species that are threatened, rare or simply unavailable.

Although not yet widely available, lab-cultured beef, chicken, lamb and shrimp, for instance, have already been developed. Several countries have invested heavily in the sector and are currently testing for safety, developing policies and guidelines and working towards accurate labelling before legislation is passed.

That said, lab-cultured chicken has been available in Singapore since 2020, and approved to be safe for public consumption in 2023 by the USDA and FDA in the US. Many countries in Europe, like the Netherlands and Norway, are at advanced stages of the safety and approval process, along with the UK, China, Japan and several others.

Conversely, Italy has taken the bold step of banning cultivated meats for now, citing safety concerns, and preferring to protect farmers and their culinary heritage instead.

Read more in Daily Maverick: Lab-grown beef and venison steaks could help save the planet

While significant gains have been made, many barriers must still be overcome for the technology to reach scale, for more companies to reach proof of concept for a wider range of proteins, and for these to reach the market. The cost of developing the technology and reaching proof of concept is coming down, and we’re getting more efficient in terms of the energy requirements for such systems.

Nevertheless, sourcing the appropriate stem cells and developing and optimising standard media formulations for a variety of cell types remain considerable challenges, along with scaffold technologies to support cell proliferation and bioreactor design and function to produce cells at scale.

It has become astonishingly easier to model proteins and forecast chemistry using smarter, adapted AI applications.

We cannot afford to take scientific “short-cuts” in the development of this technology. For example, genetic modification would be a relatively easily achievable hack to create cells that respond and proliferate at accelerated rates in a standard growth medium. We can also use media with synthetically produced growth factors from genetic modification, or animal-derived scaffolds for cell adhesion, to give shape to the final product.

However, the premise upon which cultivated proteins is built is safety, sustainability and long-term benefit for consumers and the environment, and to have zero impact on animals – apart from sourcing stem cells through biopsies, which has little effect on the animal from which these are sourced.

Yet we now find ourselves in the most exciting phase in the development of this technology. The combination of our biotech knowledge with the recent developments in artificial intelligence (AI) will provide a tremendous boost to cellular agriculture in the months and years ahead.

It has become astonishingly easier to model proteins and forecast chemistry using smarter, adapted AI applications. Companies that can effectively leverage AI will flatten barriers, saving months of research and development time.

Harnessing AI to better understand and predict protein structure and function, for example through the AlphaFold database, was not available to scientists just a few years ago. We can now anticipate and predict potential protein-folding anomalies to address health and safety concerns far earlier in the developmental process.

Prediction, through AI, of genetic make-up and expression will yield candidate stem cells in significantly shorter times. We can also use AI to explore new culture media formulations and predict, to some extent, cellular response to media components which will greatly improve our efforts at scaling up.

The masses of data generated from past and ongoing experiments are being analysed and interpreted in new ways, offering insights that researchers have missed along the way. Ultimately, we are now in a better position to automate cellular agricultural processes, gaining more precise control over the growth conditions and cell developmental processes.

Of particular interest to South Africa is the opportunity, through cellular agriculture, to relieve pressure on our especially sensitive ecosystems and coastline.

This will translate to products that match natural meats more closely in terms of texture, composition (muscle-to-fat ratio, for example) and taste. 

With the assistance of AI, the costs of cellular agriculture in terms of resources needed and time, are rapidly reducing, which will translate to greater accessibility once it reaches the global market. What remains is to understand the market demands and uptake.

Present research has focused primarily on the willingness of consumers to try the product, which is by no means an indicator of regular consumption or intention to switch from conventional meats. Here again AI presents opportunities to gain consumer insights and sentiment analysis by modelling and predicting consumer behaviour from data sources that were previously inaccessible.   

Read more in Daily Maverick: Lab-grown meat can be kosher and halal, experts say

The field of cellular agriculture, as with all industries, has much to gain from implementing AI in smarter and more novel ways. We are likely to see far superior products far sooner than anticipated from researchers who can harness the full spectrum of technologies currently on offer – and to come.

Of particular interest to South Africa is the opportunity, through cellular agriculture, to relieve pressure on our especially sensitive ecosystems and coastline.

Lab-cultured abalone, for example, is a very real possibility, as is fish protein from species that are threatened, rare or simply unavailable. We must see increased investments in this sector and more companies and researchers entering the space. DM

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  • James Baxter says:

    There is a bit of techno optimism that may be a contributing factor in these emerging technology not living up to their potential. Last time it was Blockchain and the time before that it was web 2.0;or 3.0. If it took life 3 billion years to develop a workable nervous system, I think it is naive for us to assume that AI would suddenly become this self aware technology capable of taking us to the proverbial utopia. For AI to get where we want it to get we have to first understand or fully comprehend the inner workings of molecular biology or have the capacity to operate at molecular scales. Be able to build artificial nano structures, these nano structures hopefully will be able to function as hardware for AI. The current hardware structure of Morden technology being chips, are not capable of supporting AI in it’s full potential. What we need is a new technology framework founded on quantum mechanics, because consciousness according to amateurish understanding of the interaction between matter anf energy stems from the point where these two forces continually morph into and out of matter/energy. Or maybe I am rumbling intellectually.

    • Michele Rivarola says:

      Current systems have no intelligence, they are binary systems and just have the capacity and ability of processing huge amounts of data is a short time because of the ability to retrieve information quickly. Our brain is fastest at tasks that are performed frequently (walking, talking, seeing etc.) but not as fast at where selection from existing data banks is required and once again I speak of two dimensional operations, once you add a third dimension so called AI is nowhere to be seen. Machine learning is based on expanding the data from which a two dimensional machine choses it is not in any way adding a third layer of choice or knowledge. Quantum based systems may very well change all that because of their multi-dimensional states and properties fortunately I will be probably pushing daises by then.

  • Catherine Royce says:

    This explanation of how AI can be applied in food science is welcome, thanks.

  • Robert Fincham says:

    A thought-provoking article by Prof Nakhooda on advances in biotech and AI. The relevance to addressing multiple issues concurrently is particularly exciting. Contemporary agriculture and changes to ways of producing food have serious impacts on biodiversity and human health. Climate change adds another dimension of concern.
    James Baxter’s comments are also important in thinking about the impact of new technologies and AI. The research direction of Prof Nakhooda’s work is exciting. However, the adage that we use technologies and new products that have had unforeseen and sizeable unwanted impacts, is so true. The pesticide, DDT is an example. There were many photos of children in New York running with glee through streams of the pesticide from tankers in its starting years. It was considered so safe! Now its use is drastically curtailed. Using it indoors to combat malaria in African contexts still is one of WHOs happy spaces for it. Its safety and environmental impact are balanced against the ravages of malaria.
    We need to hear more about the monitoring and evaluation protocols of these products and AI. Learning about potential impacts should occur from start to release of products to the public. We need a strong communication strategy from scientists. They should regard it as a task to creates learning and understanding about this emerging field of biotech for the public, as this article begins to do. As the author Covey has said, the biggest communication problem is that we do not listen to understand, we listen to reply. The integrity and trust of researchers by the public is an issue that we need to recognise. Enthusiasm to explore scientific boundaries should not outweigh the often-difficult commitment to communicate the findings of that exploration to the public. As scientists it must be about listening to understand the views of others about their work.

  • Gavin Hillyard says:

    What we need is fewer people to feed, not more food to feed more people. I understand that Elon Musk stated that AI is the biggest threat to the human race and I believe him.

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