Peanut allergies affect about a million children in the U.S., and most never outgrow them. Luckily, some promising remedies are in the works.
Ever since he was a baby, Sharon Wong’s son Brandon suffered from rashes, prolonged respiratory issues and vomiting. In 2006, as a young child, he was diagnosed with a severe peanut allergy.
"My son had a history of reacting to traces of peanuts in the air or in food,” says Wong, a food allergy advocate who runs a blog focusing on nut free recipes, cooking techniques and food allergy awareness. “Any participation in school activities, social events, or travel with his peanut allergy required a lot of preparation.”
Peanut allergies affect around a million children in the U.S. Most never outgrow the condition. The problem occurs when the immune system mistakenly views the proteins in peanuts as a threat and releases chemicals to counteract it. This can lead to digestive problems, hives and shortness of breath. For some, like Wong’s son, even exposure to trace amounts of peanuts could be life threatening. They go into anaphylactic shock and need to take a shot of adrenaline as soon as possible.
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.”
A future app may help you avoid getting the flu by informing you of your local risk on a given day.
Applied mathematician Sara del Valle works at the U.S.'s foremost nuclear weapons lab: Los Alamos. Once colloquially called Atomic City, it's a hidden place 45 minutes into the mountains northwest of Santa Fe. Here, engineers developed the first atomic bomb.
Like AccuWeather, an app for disease prediction could help people alter their behavior to live better lives.
Today, Los Alamos still a small science town, though no longer a secret, nor in the business of building new bombs. Instead, it's tasked with, among other things, keeping the stockpile of nuclear weapons safe and stable: not exploding when they're not supposed to (yes, please) and exploding if someone presses that red button (please, no).
Del Valle, though, doesn't work on any of that. Los Alamos is also interested in other kinds of booms—like the explosion of a contagious disease that could take down a city. Predicting (and, ideally, preventing) such epidemics is del Valle's passion. She hopes to develop an app that's like AccuWeather for germs: It would tell you your chance of getting the flu, or dengue or Zika, in your city on a given day. And like AccuWeather, it could help people alter their behavior to live better lives, whether that means staying home on a snowy morning or washing their hands on a sickness-heavy commute.
Sara del Valle of Los Alamos is working to predict and prevent epidemics using data and machine learning.
Since the beginning of del Valle's career, she's been driven by one thing: using data and predictions to help people behave practically around pathogens. As a kid, she'd always been good at math, but when she found out she could use it to capture the tentacular spread of disease, and not just manipulate abstractions, she was hooked.
When she made her way to Los Alamos, she started looking at what people were doing during outbreaks. Using social media like Twitter, Google search data, and Wikipedia, the team started to sift for trends. Were people talking about hygiene, like hand-washing? Or about being sick? Were they Googling information about mosquitoes? Searching Wikipedia for symptoms? And how did those things correlate with the spread of disease?
It was a new, faster way to think about how pathogens propagate in the real world. Usually, there's a 10- to 14-day lag in the U.S. between when doctors tap numbers into spreadsheets and when that information becomes public. By then, the world has moved on, and so has the disease—to other villages, other victims.
"We found there was a correlation between actual flu incidents in a community and the number of searches online and the number of tweets online," says del Valle. That was when she first let herself dream about a real-time forecast, not a 10-days-later backcast. Del Valle's group—computer scientists, mathematicians, statisticians, economists, public health professionals, epidemiologists, satellite analysis experts—has continued to work on the problem ever since their first Twitter parsing, in 2011.
They've had their share of outbreaks to track. Looking back at the 2009 swine flu pandemic, they saw people buying face masks and paying attention to the cleanliness of their hands. "People were talking about whether or not they needed to cancel their vacation," she says, and also whether pork products—which have nothing to do with swine flu—were safe to buy.
At the latest meeting with all the prediction groups, del Valle's flu models took first and second place.
They watched internet conversations during the measles outbreak in California. "There's a lot of online discussion about anti-vax sentiment, and people trying to convince people to vaccinate children and vice versa," she says.
Today, they work on predicting the spread of Zika, Chikungunya, and dengue fever, as well as the plain old flu. And according to the CDC, that latter effort is going well.
Since 2015, the CDC has run the Epidemic Prediction Initiative, a competition in which teams like de Valle's submit weekly predictions of how raging the flu will be in particular locations, along with other ailments occasionally. Michael Johannson is co-founder and leader of the program, which began with the Dengue Forecasting Project. Its goal, he says, was to predict when dengue cases would blow up, when previously an area just had a low-level baseline of sick people. "You'll get this massive epidemic where all of a sudden, instead of 3,000 to 4,000 cases, you have 20,000 cases," he says. "They kind of come out of nowhere."
But the "kind of" is key: The outbreaks surely come out of somewhere and, if scientists applied research and data the right way, they could forecast the upswing and perhaps dodge a bomb before it hit big-time. Questions about how big, when, and where are also key to the flu.
A big part of these projects is the CDC giving the right researchers access to the right information, and the structure to both forecast useful public-health outcomes and to compare how well the models are doing. The extra information has been great for the Los Alamos effort. "We don't have to call departments and beg for data," says del Valle.
When data isn't available, "proxies"—things like symptom searches, tweets about empty offices, satellite images showing a green, wet, mosquito-friendly landscape—are helpful: You don't have to rely on anyone's health department.
At the latest meeting with all the prediction groups, del Valle's flu models took first and second place. But del Valle wants more than weekly numbers on a government website; she wants that weather-app-inspired fortune-teller, incorporating the many diseases you could get today, standing right where you are. "That's our dream," she says.
This plot shows the the correlations between the online data stream, from Wikipedia, and various infectious diseases in different countries. The results of del Valle's predictive models are shown in brown, while the actual number of cases or illness rates are shown in blue.
(Courtesy del Valle)
The goal isn't to turn you into a germophobic agoraphobe. It's to make you more aware when you do go out. "If you know it's going to rain today, you're more likely to bring an umbrella," del Valle says. "When you go on vacation, you always look at the weather and make sure you bring the appropriate clothing. If you do the same thing for diseases, you think, 'There's Zika spreading in Sao Paulo, so maybe I should bring even more mosquito repellent and bring more long sleeves and pants.'"
They're not there yet (don't hold your breath, but do stop touching your mouth). She estimates it's at least a decade away, but advances in machine learning could accelerate that hypothetical timeline. "We're doing baby steps," says del Valle, starting with the flu in the U.S., dengue in Brazil, and other efforts in Colombia, Ecuador, and Canada. "Going from there to forecasting all diseases around the globe is a long way," she says.
But even AccuWeather started small: One man began predicting weather for a utility company, then helping ski resorts optimize their snowmaking. His influence snowballed, and now private forecasting apps, including AccuWeather's, populate phones across the planet. The company's progression hasn't been without controversy—privacy incursions, inaccuracy of long-term forecasts, fights with the government—but it has continued, for better and for worse.
Disease apps, perhaps spun out of a small, unlikely team at a nuclear-weapons lab, could grow and breed in a similar way. And both the controversies and public-health benefits that may someday spin out of them lie in the future, impossible to predict with certainty.