Lab-grown meat will soon be sold in the U.S., but who will buy It?
Last November, when the U.S. Food and Drug Administration disclosed that chicken from a California firm called UPSIDE Foods did not raise safety concerns, it drily upended how humans have obtained animal protein for thousands of generations.
“The FDA is ready to work with additional firms developing cultured animal cell food and production processes to ensure their food is safe and lawful,” the agency said in a statement at the time.
Assuming UPSIDE obtains clearances from the U.S. Department of Agriculture, its chicken – grown entirely in a laboratory without harming a single bird – could be sold in supermarkets in the coming months.
“Ultimately, we want our products to be available everywhere meat is sold, including retail and food service channels,” a company spokesperson said. The upscale French restaurant Atelier Crenn in San Francisco will have UPSIDE chicken on its menu once it is approved, she added.
Known as lab-grown or cultured meat, a product such as UPSIDE’s is created using stem cells and other tissue obtained from a chicken, cow or other livestock. Those cells are then multiplied in a nutrient-dense environment, usually in conjunction with a “scaffold” of plant-based materials or gelatin to give them a familiar form, such as a chicken breast or a ribeye steak. A Dutch company called Mosa Meat claims it can produce 80,000 hamburgers derived from a cluster of tissue the size of a sesame seed.
Critics say the doubts about lab-grown meat and the possibility it could merge “Brave New World” with “The Jungle” and “Soylent Green” have not been appropriately explored.
That’s a far cry from when it took months of work to create the first lab-grown hamburger a decade ago. That minuscule patty – which did not contain any fat and was literally plucked from a Petri dish to go into a frying pan – cost about $325,000 to produce.
Just a decade later, an Israeli company called Future Meat said it can produce lab-grown meat for about $1.70 per pound. It plans to open a production facility in the U.S. sometime in 2023 and distribute its products under the brand name “Believer.”
Costs for production have sunk so low that researchers at Carnegie Mellon University in Pittsburgh expect sometime in early 2024 to produce lab-grown Wagyu steak to showcase the viability of growing high-end cuts of beef cheaply. The Carnegie Mellon team is producing its Wagyu using a consumer 3-D printer bought secondhand on eBay and modified to print the highly marbled flesh using a method developed by the university. The device costs $200 – about the same as a pound of Wagyu in the U.S. The initiative’s modest five-figure budget was successfully crowdfunded last year.
“The big cost is going to be the cells (which are being extracted by a cow somewhere in Pennsylvania), but otherwise printing doesn’t add much to the process,” said Rosalyn Abbott, a Carnegie Mellon assistant professor of bioengineering who is co-leader on the project. “But it adds value, unlike doing this with ground meat.”
Lab-Grown Meat’s Promise
Proponents of lab-grown meat say it will cut down on traditional agriculture, which has been a leading contributor to deforestation, water shortages and contaminated waterways from animal waste, as well as climate change.
An Oxford University study from 2011 concludes lab-grown meat could have greenhouse emissions 96 percent lower compared to traditionally raised livestock. Moreover, proponents of lab-grown meat claim that the suffering of animals would decline dramatically, as they would no longer need to be warehoused and slaughtered. A recently opened 26-story high-rise in China dedicated to the raising and slaughtering of pigs illustrates the current plight of livestock in stark terms.
Scientists may even learn how to tweak lab-grown meat to make it more nutritious. Natural red meat is high in saturated fat and, if it’s eaten too often, can lead to chronic diseases. In lab versions, the saturated fat could be swapped for healthier, omega-3 fatty acids.
But critics say the doubts about lab-grown meat and the possibility it could merge “Brave New World” with “The Jungle” and “Soylent Green” have not been appropriately explored.
A Slippery Slope?
Some academics who have studied the moral and ethical issues surrounding lab-grown meat believe it will have a tough path ahead gaining acceptance by consumers. Should it actually succeed in gaining acceptance, many ethical questions must be answered.
“People might be interested” in lab-grown meat, perhaps as a curiosity, said Carlos Alvaro, an associate professor of philosophy at the New York City College of Technology, part of the City University of New York. But the allure of traditionally sourced meat has been baked – or perhaps grilled – into people’s minds for so long that they may not want to make the switch. Plant-based meat provides a recent example of the uphill battle involved in changing old food habits, with Beyond Meat’s stock prices dipping nearly 80 percent in 2022.
"There are many studies showing that people don’t really care about the environment (to that extent)," Alvaro said. "So I don’t know how you would convince people to do this because of the environment.”
“From my research, I understand that the taste (of lab-grown meat) is not quite there,” Alvaro said, noting that the amino acids, sugars and other nutrients required to grow cultivated meat do not mimic what livestock are fed. He also observed that the multiplication of cells as part of the process “really mimic cancer cells” in the way they grow, another off-putting thought for would-be consumers of the product.
Alvaro is also convinced the public will not buy into any argument that lab-grown meat is more environmentally friendly.
“If people care about the environment, they either try and consume considerably less meat and other animal products, or they go vegan or vegetarian,” he said. “But there are many studies showing that people don’t really care about the environment (to that extent). So I don’t know how you would convince people to do this because of the environment.”
Ben Bramble, a professor at Australian National University who previously held posts at Princeton and Trinity College in Ireland, takes a slightly different tack. He noted that “if lab-grown meat becomes cheaper, healthier, or tastier than regular meat, there will be a large market for it. If it becomes all of these things, it will dominate the market.”
However, Bramble has misgivings about that occurring. He believes a smooth transition from traditionally sourced meat to a lab-grown version would allow humans to elide over the decades of animal cruelty perpetrated by large-scale agriculture, without fully reckoning with and learning from this injustice.
“My fear is that if we all switch over to lab-grown meat because it has become cheaper, healthier, or tastier than regular meat, we might never come to realize what we have done, and the terrible things we are capable of,” he said. “This would be a catastrophe.”
Bramble’s writings about cultured meat also raise some serious moral conundrums. If, for example, animal meat may be cultivated without killing animals, why not create products from human protein?
Actually, that’s already happened.
It occurred in 2019, when Orkan Telhan, a professor of fine arts at the University of Pennsylvania, collaborated with two scientists to create an art exhibit at the Philadelphia Museum of Art on the future of foodstuffs.
Although the exhibit included bioengineered bread and genetically modified salmon, it was an installation called “Ouroboros Steak” that drew the most attention. That was comprised of pieces of human flesh grown in a lab from cultivated cells and expired blood products obtained from online sources.
The exhibit was presented as four tiny morsels of red meat – shaped in patterns suggesting an ouroboros, a dragon eating its own tail. They were placed in tiny individual saucers atop a larger plate and placemat with a calico pattern, suggesting an item to order in a diner. The artwork drew international headlines – as well as condemnation for Telhan’s vision.
Telhan’s artwork is intended to critique the overarching assumption that lab-grown meat will eventually replace more traditional production methods, as well as the lack of transparency surrounding many processed foodstuffs. “They think that this problem (from industrial-scale agriculture) is going be solved by this new technology,” Telhan said. “I am critical (of) that perspective.”
Unlike Bramble, Telhan is not against lab-grown meat, so long as its producers are transparent about the sourcing of materials and its cultivation. But he believes that large-scale agricultural meat production – which dates back centuries – is not going to be replaced so quickly.
“We see this again and again with different industries, like algae-based fuels. A lot of companies were excited about this, and promoted it,” Telhan said. “And years later, we know these fuels work. But to be able to displace the oil industry means building the infrastructure to scale takes billions of dollars, and nobody has the patience or money to do it.”
Alvaro concurred on this point, which he believes is already weakened because a large swath of consumers aren’t concerned about environmental degradation.
“They’re going to have to sell this big, but in order to convince people to do so, they have to convince them to eat this product instead of regular meat,” Alvaro said.
Hidden Tweaks?
Moreover, if lab-based meat does obtain a significant market share, Telhan suggested companies may do things to the product – such as to genetically modify it to become more profitable – and never notify consumers. That is a particular concern in the U.S., where regulations regarding such modifications are vastly more relaxed than in the European Union.
“I think that they have really good objectives, and they aspire to good objectives,” Telhan said. “But the system itself doesn't really allow for that much transparency.”
No matter what the future holds, sometime next year Carnegie Mellon is expected to hold a press conference announcing it has produced a cut of the world’s most expensive beef with the help of a modified piece of consumer electronics. It will likely take place at around the same time UPSIDE chicken will be available for purchase in supermarkets and restaurants, pending the USDA’s approvals.
Abbott, the Carnegie Mellon professor, suggested the future event will be both informative and celebratory.
“I think Carnegie Mellon would have someone potentially cook it for us,” she said. “Like have a really good chef in New York City do it.”
Two years, six million deaths and still counting, scientists are searching for answers to prevent another COVID-19-like tragedy from ever occurring again. And it’s a gargantuan task.
Our disturbed ecosystems are creating more favorable conditions for the spread of infectious disease. Global warming, deforestation, rising sea levels and flooding have contributed to a rise in mosquito-borne infections and longer tick seasons. Disease-carrying animals are in closer range to other species and humans as they migrate to escape the heat. Bats are thought to have carried the SARS-CoV-2 virus to Wuhan, either directly or through another host animal, but thousands of novel viruses are lurking within other wild creatures.
Understanding how climate change contributes to the spread of disease is critical in predicting and thwarting future calamities. But the problem is that predictive models aren’t yet where they need to be for forecasting with certainty beyond the next year, as we could for weather, for instance.
The association between climate and infectious disease is poorly understood, says Irina Tezaur, a computational scientist at Sandia National Laboratories. “Correlations have been observed but it’s not known if these correlations translate to causal relationships.”
To make accurate longer-term predictions, scientists need more empirical data, multiple datasets specific to locations and diseases, and the ability to calculate risks that depend on unpredictable nature and human behavior. Another obstacle is that climate scientists and epidemiologists are not collaborating effectively, so some researchers are calling for a multidisciplinary approach, a new field called Outbreak Science.
Climate scientists are far ahead of epidemiologists in gathering essential data.
Earth System Models—combining the interactions of atmosphere, ocean, land, ice and biosphere—have been in place for two decades to monitor the effects of global climate change. These models must be combined with epidemiological and human model research, areas that are easily skewed by unpredictable elements, from extreme weather events to public environmental policy shifts.
“There is never just one driver in tracking the impact of climate on infectious disease,” says Joacim Rocklöv, a professor at the Heidelberg Institute of Global Health & Heidelberg Interdisciplinary Centre for Scientific Computing in Germany. Rocklöv has studied how climate affects vector-borne diseases—those transmitted to humans by mosquitoes, ticks or fleas. “You need to disentangle the variables to find out how much difference climate makes to the outcome and how much is other factors.” Determinants from deforestation to population density to lack of healthcare access influence the spread of disease.
Even though climate change is not the primary driver of infectious disease today, it poses a major threat to public health in the future, says Rocklöv.
The promise of predictive modeling
“Models are simplifications of a system we’re trying to understand,” says Jeremy Hess, who directs the Center for Health and the Global Environment at University of Washington in Seattle. “They’re tools for learning that improve over time with new observations.”
Accurate predictions depend on high-quality, long-term observational data but models must start with assumptions. “It’s not possible to apply an evidence-based approach for the next 40 years,” says Rocklöv. “Using models to experiment and learn is the only way to figure out what climate means for infectious disease. We collect data and analyze what already happened. What we do today will not make a difference for several decades.”
To improve accuracy, scientists develop and draw on thousands of models to cover as many scenarios as possible. One model may capture the dynamics of disease transmission while another focuses on immunity data or ocean influences or seasonal components of a virus. Further, each model needs to be disease-specific and often location-specific to be useful.
“All models have biases so it’s important to use a suite of models,” Tezaur stresses.
The modeling scientist chooses the drivers of change and parameters based on the question explored. The drivers could be increased precipitation, poverty or mosquito prevalence, for instance. Later, the scientist may need to isolate the effect of one driver so that will require another model.
There have been some related successes, such as the latest models for mosquito-borne diseases like Dengue, Zika and malaria as well as those for flu and tick-borne diseases, says Hess.
Rocklöv was part of a research team that used test data from 2018 and 2019 to identify regions at risk for West Nile virus outbreaks. Using AI, scientists were able to forecast outbreaks of the virus for the entire transmission season in Europe. “In the end, we want data-driven models; that’s what AI can accomplish,” says Rocklöv. Other researchers are making an important headway in creating a framework to predict novel host–parasite interactions.
Modeling studies can run months, years or decades. “The scientist is working with layers of data. The challenge is how to transform and couple different models together on a planetary scale,” says Jeanne Fair, a scientist at Los Alamos National Laboratory, Biosecurity and Public Health, in New Mexico.
Disease forecasting will require a significant investment into the infrastructure needed to collect data about the environment, vectors, and hosts a tall spatial and temporal resolutions.
And it’s a constantly changing picture. A modeling study in an April 2022 issue of Nature predicted that thousands of animals will migrate to cooler locales as temperatures rise. This means that various species will come into closer contact with people and other mammals for the first time. This is likely to increase the risk of emerging infectious disease transmitted from animals to humans, especially in Africa and Asia.
Other things can happen too. Global warming could precipitate viral mutations or new infectious diseases that don’t respond to antimicrobial treatments. Insecticide-resistant mosquitoes could evolve. Weather-related food insecurity could increase malnutrition and weaken people’s immune systems. And the impact of an epidemic will be worse if it co-occurs during a heatwave, flood, or drought, says Hess.
The devil is in the climate variables
Solid predictions about the future of climate and disease are not possible with so many uncertainties. Difficult-to-measure drivers must be added to the empirical model mix, such as land and water use, ecosystem changes or the public’s willingness to accept a vaccine or practice social distancing. Nor is there any precedent for calculating the effect of climate changes that are accelerating at a faster speed than ever before.
The most critical climate variables thought to influence disease spread are temperature, precipitation, humidity, sunshine and wind, according to Tezaur’s research. And then there are variables within variables. Influenza scientists, for example, found that warm winters were predictors of the most severe flu seasons in the following year.
The human factor may be the most challenging determinant. To what degree will people curtail greenhouse gas emissions, if at all? The swift development of effective COVID-19 vaccines was a game-changer, but will scientists be able to repeat it during the next pandemic? Plus, no model could predict the amount of internet-fueled COVID-19 misinformation, Fair noted. To tackle this issue, infectious disease teams are looking to include more sociologists and political scientists in their modeling.
Addressing the gaps
Currently, researchers are focusing on the near future, predicting for next year, says Fair. “When it comes to long-term, that’s where we have the most work to do.” While scientists cannot foresee how political influences and misinformation spread will affect models, they are positioned to make headway in collecting and assessing new data streams that have never been merged.
Disease forecasting will require a significant investment into the infrastructure needed to collect data about the environment, vectors, and hosts at all spatial and temporal resolutions, Fair and her co-authors stated in their recent study. For example real-time data on mosquito prevalence and diversity in various settings and times is limited or non-existent. Fair also would like to see standards set in mosquito data collection in every country. “Standardizing across the US would be a huge accomplishment,” she says.
Understanding how climate change contributes to the spread of disease is critical for thwarting future calamities.
Jeanne Fair
Hess points to a dearth of data in local and regional datasets about how extreme weather events play out in different geographic locations. His research indicates that Africa and the Middle East experienced substantial climate shifts, for example, but are unrepresented in the evidentiary database, which limits conclusions. “A model for dengue may be good in Singapore but not necessarily in Port-au-Prince,” Hess explains. And, he adds, scientists need a way of evaluating models for how effective they are.
The hope, Rocklöv says, is that in the future we will have data-driven models rather than theoretical ones. In turn, sharper statistical analyses can inform resource allocation and intervention strategies to prevent outbreaks.
Most of all, experts emphasize that epidemiologists and climate scientists must stop working in silos. If scientists can successfully merge epidemiological data with climatic, biological, environmental, ecological and demographic data, they will make better predictions about complex disease patterns. Modeling “cross talk” and among disciplines and, in some cases, refusal to release data between countries is hindering discovery and advances.
It’s time for bold transdisciplinary action, says Hess. He points to initiatives that need funding in disease surveillance and control; developing and testing interventions; community education and social mobilization; decision-support analytics to predict when and where infections will emerge; advanced methodologies to improve modeling; training scientists in data management and integrated surveillance.
Establishing a new field of Outbreak Science to coordinate collaboration would accelerate progress. Investment in decision-support modeling tools for public health teams, policy makers, and other long-term planning stakeholders is imperative, too. We need to invest in programs that encourage people from climate modeling and epidemiology to work together in a cohesive fashion, says Tezaur. Joining forces is the only way to solve the formidable challenges ahead.
This article originally appeared in One Health/One Planet, a single-issue magazine that explores how climate change and other environmental shifts are increasing vulnerabilities to infectious diseases by land and by sea. The magazine probes how scientists are making progress with leaders in other fields toward solutions that embrace diverse perspectives and the interconnectedness of all lifeforms and the planet.
Scientists use AI to predict how hospital stays will go
The Friday Five covers five stories in research that you may have missed this week. There are plenty of controversies and troubling ethical issues in science – and we get into many of them in our online magazine – but this news roundup focuses on scientific creativity and progress to give you a therapeutic dose of inspiration headed into the weekend.
Here are the promising studies covered in this week's Friday Five:
- The problem with bedtime munching
- Scientists use AI to predict how stays in hospitals will go
- How to armor the shields of our livers against cancer
- One big step to save the world: turn one kind of plastic into another
- The perfect recipe for tiny brains
And an honorable mention this week: Bigger is better when it comes to super neurons in super agers