Peanut allergies affect about a million children in the U.S., and most never outgrow them. Luckily, some promising remedies are in the works.
Typically, people with peanut allergies try to completely avoid them and carry an adrenaline autoinjector like an EpiPen in case of emergencies. This constant vigilance is very stressful, particularly for parents with young children.
“The search for a peanut allergy ‘cure’ has been a vigorous one,” says Claudia Gray, a pediatrician and allergist at Vincent Pallotti Hospital in Cape Town, South Africa. The closest thing to a solution so far, she says, is the process of desensitization, which exposes the patient to gradually increasing doses of peanut allergen to build up a tolerance. The most common type of desensitization is oral immunotherapy, where patients ingest small quantities of peanut powder. It has been effective but there is a risk of anaphylaxis since it involves swallowing the allergen.
"By the end of the trial, my son tolerated approximately 1.5 peanuts," Sharon Wong says.
DBV Technologies, a company based in Montrouge, France has created a skin patch to address this problem. The Viaskin Patch contains a much lower amount of peanut allergen than oral immunotherapy and delivers it through the skin to slowly increase tolerance. This decreases the risk of anaphylaxis.
Wong heard about the peanut patch and wanted her son to take part in an early phase 2 trial for 4-to-11-year-olds.
“We felt that participating in DBV’s peanut patch trial would give him the best chance at desensitization or at least increase his tolerance from a speck of peanut to a peanut,” Wong says. “The daily routine was quite simple, remove the old patch and then apply a new one. By the end of the trial, he tolerated approximately 1.5 peanuts.”
How it works
For DBV Technologies, it all began when pediatric gastroenterologist Pierre-Henri Benhamou teamed up with fellow professor of gastroenterology Christopher Dupont and his brother, engineer Bertrand Dupont. Together they created a more effective skin patch to detect when babies have allergies to cow's milk. Then they realized that the patch could actually be used to treat allergies by promoting tolerance. They decided to focus on peanut allergies first as the more dangerous.
The Viaskin patch utilizes the fact that the skin can promote tolerance to external stimuli. The skin is the body’s first defense. Controlling the extent of the immune response is crucial for the skin. So it has defense mechanisms against external stimuli and can promote tolerance.
The patch consists of an adhesive foam ring with a plastic film on top. A small amount of peanut protein is placed in the center. The adhesive ring is attached to the back of the patient's body. The peanut protein sits above the skin but does not directly touch it. As the patient sweats, water droplets on the inside of the film dissolve the peanut protein, which is then absorbed into the skin.
The peanut protein is then captured by skin cells called Langerhans cells. They play an important role in getting the immune system to tolerate certain external stimuli. Langerhans cells take the peanut protein to lymph nodes which activate T regulatory cells. T regulatory cells suppress the allergic response.
A different patch is applied to the skin every day to increase tolerance. It’s both easy to use and convenient.
“The DBV approach uses much smaller amounts than oral immunotherapy and works through the skin significantly reducing the risk of allergic reactions,” says Edwin H. Kim, the division chief of Pediatric Allergy and Immunology at the University of North Carolina, U.S., and one of the principal investigators of Viaskin’s clinical trials. “By not going through the mouth, the patch also avoids the taste and texture issues. Finally, the ability to apply a patch and immediately go about your day may be very attractive to very busy patients and families.”
Brandon Wong displaying origami figures he folded at an Origami Convention in 2022
Sharon Wong
Clinical trials
Results from DBV's phase 3 trial in children ages 1 to 3 show its potential. For a positive result, patients who could not tolerate 10 milligrams or less of peanut protein had to be able to manage 300 mg or more after 12 months. Toddlers who could already tolerate more than 10 mg needed to be able to manage 1000 mg or more. In the end, 67 percent of subjects using the Viaskin patch met the target as compared to 33 percent of patients taking the placebo dose.
“The Viaskin peanut patch has been studied in several clinical trials to date with promising results,” says Suzanne M. Barshow, assistant professor of medicine in allergy and asthma research at Stanford University School of Medicine in the U.S. “The data shows that it is safe and well-tolerated. Compared to oral immunotherapy, treatment with the patch results in fewer side effects but appears to be less effective in achieving desensitization.”
The primary reason the patch is less potent is that oral immunotherapy uses a larger amount of the allergen. Additionally, absorption of the peanut protein into the skin could be erratic.
Gray also highlights that there is some tradeoff between risk and efficacy.
“The peanut patch is an exciting advance but not as effective as the oral route,” Gray says. “For those patients who are very sensitive to orally ingested peanut in oral immunotherapy or have an aversion to oral peanut, it has a use. So, essentially, the form of immunotherapy will have to be tailored to each patient.” Having different forms such as the Viaskin patch which is applied to the skin or pills that patients can swallow or dissolve under the tongue is helpful.
The hope is that the patch’s efficacy will increase over time. The team is currently running a follow-up trial, where the same patients continue using the patch.
“It is a very important study to show whether the benefit achieved after 12 months on the patch stays stable or hopefully continues to grow with longer duration,” says Kim, who is an investigator in this follow-up trial.
"My son now attends university in Massachusetts, lives on-campus, and eats dorm food. He has so much more freedom," Wong says.
The team is further ahead in the phase 3 follow-up trial for 4-to-11-year-olds. The initial phase 3 trial was not as successful as the trial for kids between one and three. The patch enabled patients to tolerate more peanuts but there was not a significant enough difference compared to the placebo group to be definitive. The follow-up trial showed greater potency. It suggests that the longer patients are on the patch, the stronger its effects.
They’re also testing if making the patch bigger, changing the shape and extending the minimum time it’s worn can improve its benefits in a trial for a new group of 4-to-11 year-olds.
The future
DBV Technologies is using the skin patch to treat cow’s milk allergies in children ages 1 to 17. They’re currently in phase 2 trials.
As for the peanut allergy trials in toddlers, the hope is to see more efficacy soon.
For Wong’s son who took part in the earlier phase 2 trial for 4-to-11-year-olds, the patch has transformed his life.
“My son continues to maintain his peanut tolerance and is not affected by peanut dust in the air or cross-contact,” Wong says. ”He attends university in Massachusetts, lives on-campus, and eats dorm food. He still carries an EpiPen but has so much more freedom than before his clinical trial. We will always be grateful.”
Artificial Intelligence is already helping to grow some of the food we eat.
The chef-farmers choose from among 45 types of herb and leafy-greens seeds, plop them into grow trays, and a few weeks later they pick and serve. While success is predicated on at least a small amount of these humans’ care, the systems are autonomously surveilled round-the-clock from Babylon’s base of operations. And artificial intelligence is helping to run the show.
Babylon piloted the use of specialized cameras that take pictures in different spectrums to gather some less-obvious visual data about plants’ wellbeing and alert people if something seems off.
Imagine consistently perfect greens and tomatoes and strawberries, grown hyper-locally, using less water, without chemicals or environmental contaminants. This is the hefty promise of controlled environment agriculture (CEA) — basically, indoor farms that can be hydroponic, aeroponic (plant roots are suspended and fed through misting), or aquaponic (where fish play a role in fertilizing vegetables). But whether they grow 4,160 leafy-green servings per year, like one Babylon farm, or millions of servings, like some of the large, centralized facilities starting to supply supermarkets across the U.S., they seek to minimize failure as much as possible.
Babylon’s soilless hydroponic growing system
Courtesy Babylon Micro-Farms
Here, AI is starting to play a pivotal role. CEA growers use it to help “make sense of what’s happening” to the plants in their care, says Scott Lowman, vice president of applied research at the Institute for Advanced Learning and Research (IALR) in Virginia, a state that’s investing heavily in CEA companies. And although these companies say they’re not aiming for a future with zero human employees, AI is certainly poised to take a lot of human farming intervention out of the equation — for better and worse.
Most of these companies are compiling their own data sets to identify anything that might block the success of their systems. Babylon had already integrated sensor data into its farms to measure heat and humidity, the nutrient content of water, and the amount of light plants receive. Last year, they got a National Science Foundation grant that allowed them to pilot the use of specialized cameras that take pictures in different spectrums to gather some less-obvious visual data about plants’ wellbeing and alert people if something seems off. “Will this plant be healthy tomorrow? Are there things…that the human eye can't see that the plant starts expressing?” says Amandeep Ratte, the company’s head of data science. “If our system can say, Hey, this plant is unhealthy, we can reach out to [users] preemptively about what they’re doing wrong, or is there a disease at the farm?” Ratte says. The earlier the better, to avoid crop failures.
Natural light accounts for 70 percent of Greenswell Growers’ energy use on a sunny day.
Courtesy Greenswell Growers
IALR’s Lowman says that other CEA companies are developing their AI systems to account for the different crops they grow — lettuces come in all shapes and sizes, after all, and each has different growing needs than, for example, tomatoes. The ways they run their operations differs also. Babylon is unusual in its decentralized structure. But centralized growing systems with one main location have variabilities, too. AeroFarms, which recently declared bankruptcy but will continue to run its 140,000-square foot vertical operation in Danville, Virginia, is entirely enclosed and reliant on the intense violet glow of grow lights to produce microgreens.
Different companies have different data needs. What data is essential to AeroFarms isn’t quite the same as for Greenswell Growers located in Goochland County, Virginia. Raising four kinds of lettuce in a 77,000-square-foot automated hydroponic greenhouse, the vagaries of naturally available light, which accounts for 70 percent of Greenswell’s energy use on a sunny day, affect operations. Their tech needs to account for “outside weather impacts,” says president Carl Gupton. “What adjustments do we have to make inside of the greenhouse to offset what's going on outside environmentally, to give that plant optimal conditions? When it's 85 percent humidity outside, the system needs to do X, Y and Z to get the conditions that we want inside.”
AI will help identify diseases, as well as when a plant is thirsty or overly hydrated, when it needs more or less calcium, phosphorous, nitrogen.
Nevertheless, every CEA system has the same core needs — consistent yield of high quality crops to keep up year-round supply to customers. Additionally, “Everybody’s got the same set of problems,” Gupton says. Pests may come into a facility with seeds. A disease called pythium, one of the most common in CEA, can damage plant roots. “Then you have root disease pressures that can also come internally — a change in [growing] substrate can change the way the plant performs,” Gupton says.
AI will help identify diseases, as well as when a plant is thirsty or overly hydrated, when it needs more or less calcium, phosphorous, nitrogen. So, while companies amass their own hyper-specific data sets, Lowman foresees a time within the next decade “when there will be some type of [open-source] database that has the most common types of plant stress identified” that growers will be able to tap into. Such databases will “create a community and move the science forward,” says Lowman.
In fact, IALR is working on assembling images for just such a database now. On so-called “smart tables” inside an Institute lab, a team is growing greens and subjects them to various stressors. Then, they’re administering treatments while taking images of every plant every 15 minutes, says Lowman. Some experiments generate 80,000 images; the challenge lies in analyzing and annotating the vast trove of them, marking each one to reflect outcome—for example increasing the phosphate delivery and the plant’s response to it. Eventually, they’ll be fed into AI systems to help them learn.
For all the enthusiasm surrounding this technology, it’s not without downsides. Training just one AI system can emit over 250,000 pounds of carbon dioxide, according to MIT Technology Review. AI could also be used “to enhance environmental benefit for CEA and optimize [its] energy consumption,” says Rozita Dara, a computer science professor at the University of Guelph in Canada, specializing in AI and data governance, “but we first need to collect data to measure [it].”
The chef-farmers can choose from 45 types of herb and leafy-greens seeds.
Courtesy Babylon Micro-Farms
Any system connected to the Internet of Things is also vulnerable to hacking; if CEA grows to the point where “there are many of these similar farms, and you're depending on feeding a population based on those, it would be quite scary,” Dara says. And there are privacy concerns, too, in systems where imaging is happening constantly. It’s partly for this reason, says Babylon’s Ratte, that the company’s in-farm cameras all “face down into the trays, so the only thing [visible] is pictures of plants.”
Tweaks to improve AI for CEA are happening all the time. Greenswell made its first harvest in 2022 and now has annual data points they can use to start making more intelligent choices about how to feed, water, and supply light to plants, says Gupton. Ratte says he’s confident Babylon’s system can already “get our customers reliable harvests. But in terms of how far we have to go, it's a different problem,” he says. For example, if AI could detect whether the farm is mostly empty—meaning the farm’s user hasn’t planted a new crop of greens—it can alert Babylon to check “what's going on with engagement with this user?” Ratte says. “Do they need more training? Did the main person responsible for the farm quit?”
Lowman says more automation is coming, offering greater ability for systems to identify problems and mitigate them on the spot. “We still have to develop datasets that are specific, so you can have a very clear control plan, [because] artificial intelligence is only as smart as what we tell it, and in plant science, there's so much variation,” he says. He believes AI’s next level will be “looking at those first early days of plant growth: when the seed germinates, how fast it germinates, what it looks like when it germinates.” Imaging all that and pairing it with AI, “can be a really powerful tool, for sure.”
Researchers from the University of Cambridge have laid the foundations for growing synthetic embryos that could develop a beating heart, gut and brain.
The organoid revolution
In 1981, scientists discovered how to keep stem cells alive. This was a significant breakthrough, as stem cells have notoriously rigorous demands. Nevertheless, stem cells remained a relatively niche research area, mainly because scientists didn’t know how to convince the cells to turn into other cells.
Then, in 1987, scientists embedded isolated stem cells in a gelatinous protein mixture called Matrigel, which simulated the three-dimensional environment of animal tissue. The cells thrived, but they also did something remarkable: they created breast tissue capable of producing milk proteins. This was the first organoid — a clump of cells that behave and function like a real organ. The organoid revolution had begun, and it all started with a boob in Jello.
For the next 20 years, it was rare to find a scientist who identified as an “organoid researcher,” but there were many “stem cell researchers” who wanted to figure out how to turn stem cells into other cells. Eventually, they discovered the signals (called growth factors) that stem cells require to differentiate into other types of cells.
For a human embryo (and its organs) to develop successfully, there needs to be a “dialogue” between these three types of stem cells.
By the end of the 2000s, researchers began combining stem cells, Matrigel, and the newly characterized growth factors to create dozens of organoids, from liver organoids capable of producing the bile salts necessary for digesting fat to brain organoids with components that resemble eyes, the spinal cord, and arguably, the beginnings of sentience.
Synthetic embryos
Organoids possess an intrinsic flaw: they are organ-like. They share some characteristics with real organs, making them powerful tools for research. However, no one has found a way to create an organoid with all the characteristics and functions of a real organ. But Magdalena Żernicka-Goetz, a developmental biologist, might have set the foundation for that discovery.
Żernicka-Goetz hypothesized that organoids fail to develop into fully functional organs because organs develop as a collective. Organoid research often uses embryonic stem cells, which are the cells from which the developing organism is created. However, there are two other types of stem cells in an early embryo: stem cells that become the placenta and those that become the yolk sac (where the embryo grows and gets its nutrients in early development). For a human embryo (and its organs) to develop successfully, there needs to be a “dialogue” between these three types of stem cells. In other words, Żernicka-Goetz suspected the best way to grow a functional organoid was to produce a synthetic embryoid.
As described in the aforementioned Nature paper, Żernicka-Goetz and her team mimicked the embryonic environment by mixing these three types of stem cells from mice. Amazingly, the stem cells self-organized into structures and progressed through the successive developmental stages until they had beating hearts and the foundations of the brain.
“Our mouse embryo model not only develops a brain, but also a beating heart [and] all the components that go on to make up the body,” said Żernicka-Goetz. “It’s just unbelievable that we’ve got this far. This has been the dream of our community for years and major focus of our work for a decade and finally we’ve done it.”
If the methods developed by Żernicka-Goetz’s team are successful with human stem cells, scientists someday could use them to guide the development of synthetic organs for patients awaiting transplants. It also opens the door to studying how embryos develop during pregnancy.
This article originally appeared on Big Think, home of the brightest minds and biggest ideas of all time.
