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.”
Basecamp Research is using portable labs like this one to gather samples from ecosystems around the world.
Clark works for Basecamp Research, a biotech company headquartered in London, and his job is to collect samples from ecosystems around the world. By extracting DNA from soil, water, plants, microbes and other organisms, Basecamp is building an extensive database of the Earth’s proteins. While DNA itself isn’t a protein, the information stored in DNA is used to create proteins, so extracting, sequencing, and annotating DNA allows for the discovery of unique protein sequences.
Using what they’re finding in the middle of the Atlantic and beyond, Basecamp’s detailed database is constantly growing. The outputs could be essential for cleaning up the damage done by toxic chemicals and finding alternatives to these chemicals.
Catalysts for change
Proteins provide structure and function in all living organisms. Some of these functional proteins are enzymes, which quite literally make things happen.
“Industrial chemistry is heavily polluting, especially the chemistry done in pharmaceutical drug development. Biocatalysis is providing advantages, both to make more complex drugs and to be more sustainable, reducing the pollution and toxicity of conventional chemistry," says Ahir Pushpanath, who heads partnerships for Basecamp.
“Enzymes are perfectly evolved catalysts,” says Ahir Pushpanath, a partnerships lead at Basecamp. ”Enzymes are essentially just a polymer, and polymers are made up of amino acids, which are nature’s building blocks.” He suggests thinking about it like Legos — if you have a bunch of Lego pieces and use them to build a structure that performs a function, “that’s basically how an enzyme works. In nature, these monuments have evolved to do life’s chemistry. If we didn’t have enzymes, we wouldn’t be alive.”
In our own bodies, enzymes catalyze everything from vision to digesting food to regrowing muscles, and these same types of enzymes are necessary in the pharmaceutical, agrochemical and fine chemical industries. But industrial conditions differ from those inside our bodies. So, when scientists need certain chemical reactions to create a particular product or substance, they make their own catalysts in their labs — generally through the use of petroleum and heavy metals.
These petrochemicals are effective and cost-efficient, but they’re wasteful and often hazardous. With growing concerns around sustainability and long-term public health, it's essential to find alternative solutions to toxic chemicals. “Industrial chemistry is heavily polluting, especially the chemistry done in pharmaceutical drug development,” Pushpanath says.
Basecamp is trying to replace lab-created catalysts with enzymes found in the wild. This concept is called biocatalysis, and in theory, all scientists have to do is find the right enzymes for their specific need. Yet, historically, researchers have struggled to find enzymes to replace petrochemicals. When they can’t identify a suitable match, they turn to what Pushpanath describes as “long, iterative, resource-intensive, directed evolution” in the laboratory to coax a protein into industrial adaptation. But the latest scientific advances have enabled these discoveries in nature instead.
Marlon Clark, a research scientist at Basecamp Research, looks for novel biochemistries in the Azores.
Glen Gowers
Enzyme hunters
Whether it’s Clark and a colleague setting off on an expedition, or a local, on-the-ground partner gathering and processing samples, there’s a lot to be learned from each collection. “Microbial genomes contain complete sets of information that define an organism — much like how letters are a code allowing us to form words, sentences, pages, and books that contain complex but digestible knowledge,” Clark says. He thinks of the environmental samples as biological libraries, filled with thousands of species, strains, and sequence variants. “It’s our job to glean genetic information from these samples.”
“We can actually dream up new proteins using generative AI," Pushpanath says.
Basecamp researchers manage this feat by sequencing the DNA and then assembling the information into a comprehensible structure. “We’re building the ‘stories’ of the biota,” Clark says. The more varied the samples, the more valuable insights his team gains into the characteristics of different organisms and their interactions with the environment. Sequencing allows scientists to examine the order of nucleotides — the organic molecules that form DNA — to identify genetic makeups and find changes within genomes. The process used to be too expensive, but the cost of sequencing has dropped from $10,000 a decade ago to as low as $100. Notably, biocatalysis isn’t a new concept — there have been waves of interest in using natural enzymes in catalysis for over a century, Pushpanath says. “But the technology just wasn’t there to make it cost effective,” he explains. “Sequencing has been the biggest boon.”
AI is probably the second biggest boon.
“We can actually dream up new proteins using generative AI,” Pushpanath says, which means that biocataylsis now has real potential to scale.
Glen Gowers, the co-founder of Basecamp, compares the company’s AI approach to that of social networks and streaming services. Consider how these platforms suggest connecting with the friends of your friends, or how watching one comedy film from the 1990s leads to a suggestion of three more.
“They’re thinking about data as networks of relationships as opposed to lists of items,” says Gowers. “By doing the same, we’re able to link the metadata of the proteins — by their relationships to each other, the environments in which they’re found, the way those proteins might look similar in sequence and structure, their surrounding genome context — really, this just comes down to creating a searchable network of proteins.”
On an Azores island, this volcanic opening may harbor organisms that can help scientists identify enzymes for biocatalysis to replace toxic chemicals.
Emma Bolton
Uwe Bornscheuer, professor at the Institute of Biochemistry at the University of Greifswald, and co-founder of Enzymicals, another biocatalysis company, says that the development of machine learning is a critical component of this work. “It’s a very hot topic, because the challenge in protein engineering is to predict which mutation at which position in the protein will make an enzyme suitable for certain applications,” Bornscheuer explains. These predictions are difficult for humans to make at all, let alone quickly. “It is clear that machine learning is a key technology.”
Benefiting from nature’s bounty
Biodiversity commonly refers to plants and animals, but the term extends to all life, including microbial life, and some regions of the world are more biodiverse than others. Building relationships with global partners is another key element to Basecamp’s success. Doing so in accordance with the access and benefit sharing principles set forth by the Nagoya Protocol — an international agreement that seeks to ensure the benefits of using genetic resources are distributed in a fair and equitable way — is part of the company's ethos. “There's a lot of potential for us, and there’s a lot of potential for our partners to have exactly the same impact in building and discovering commercially relevant proteins and biochemistries from nature,” Clark says.
Bornscheuer points out that Basecamp is not the first company of its kind. A former San Diego company called Diversa went public in 2000 with similar work. “At that time, the Nagoya Protocol was not around, but Diversa also wanted to ensure that if a certain enzyme or microorganism from Costa Rica, for example, were used in an industrial process, then people in Costa Rica would somehow profit from this.”
An eventual merger turned Diversa into Verenium Corporation, which is now a part of the chemical producer BASF, but it laid important groundwork for modern companies like Basecamp to continue to scale with today’s technologies.
“To collect natural diversity is the key to identifying new catalysts for use in new applications,” Bornscheuer says. “Natural diversity is immense, and over the past 20 years we have gained the advantages that sequencing is no longer a cost or time factor.”
This has allowed Basecamp to rapidly grow its database, outperforming Universal Protein Resource or UniProt, which is the public repository of protein sequences most commonly used by researchers. Basecamp’s database is three times larger, totaling about 900 million sequences. (UniProt isn’t compliant with the Nagoya Protocol, because, as a public database, it doesn’t provide traceability of protein sequences. Some scientists, however, argue that Nagoya compliance hinders progress.)
“Eventually, this work will reduce chemical processes. We’ll have cleaner processes, more sustainable processes," says Uwe Bornscheuer, a professor at the University of Greifswald.
With so much information available, Basecamp’s AI has been trained on “the true dictionary of protein sequence life,” Pushpanath says, which makes it possible to design sequences for particular applications. “Through deep learning approaches, we’re able to find protein sequences directly from our database, without the need for further laboratory-directed evolution.”
Recently, a major chemical company was searching for a specific transaminase — an enzyme that catalyzes a transfer of amino groups. “They had already spent a year-and-a-half and nearly two million dollars to evolve a public-database enzyme, and still had not reached their goal,” Pushpanath says. “We used our AI approaches on our novel database to yield 10 candidates within a week, which, when validated by the client, achieved the desired target even better than their best-evolved candidate.”
Basecamp’s other huge potential is in bioremediation, where natural enzymes can help to undo the damage caused by toxic chemicals. “Biocatalysis impacts both sides,” says Gowers. “It reduces the usage of chemicals to make products, and at the same time, where contamination sites do exist from chemical spills, enzymes are also there to kind of mop those up.”
So far, Basecamp's round-the-world sampling has covered 50 percent of the 14 major biomes, or regions of the planet that can be distinguished by their flora, fauna, and climate, as defined by the World Wildlife Fund. The other half remains to be catalogued — a key milestone for understanding our planet’s protein diversity, Pushpanath notes.
There’s still a long road ahead to fully replace petrochemicals with natural enzymes, but biocatalysis is on an upward trajectory. "Eventually, this work will reduce chemical processes,” Bornscheuer says. “We’ll have cleaner processes, more sustainable processes.”
In an initial study, Canary analyzed speech recordings with AI and identified early stage Alzheimer’s with 96 percent accuracy.
Arnold was diagnosed sooner than many others. It's important to find out early, when interventions can make the most difference. One promising avenue is looking at how people talk. Research has shown that Alzheimer’s affects a part of the brain that controls speech, resulting in small changes before people show other signs of the disease.
Now, Canary Speech, a company based in Utah, is using AI to examine elements like the pitch of a person’s voice and their pauses. In an initial study, Canary analyzed speech recordings with AI and identified early stage Alzheimer’s with 96 percent accuracy.
Developing the AI model
Canary Speech’s CEO, Henry O’Connell, met cofounder Jeff Adams about 40 years before they started the company. Back when they first crossed paths, they were both living in Bethesda, Maryland; O’Connell was a research fellow at the National Institutes of Health studying rare neurological diseases, while Adams was working to decode spy messages. Later on, Adams would specialize in building mathematical models to analyze speech and sound as a team leader in developing Amazon's Alexa.
It wasn't until 2015 that they decided to make use of the fit between their backgrounds. ““We established Canary Speech in 2017 to build a product that could be used in multiple languages in clinical environments,” O'Connell says.
The need is growing. About 55 million people worldwide currently live with Alzheimer’s, a number that is expected to double by 2050. Some scientists think the disease results from a buildup of plaque in the brain. It causes mild memory loss at first and, over time, this issue get worse while other symptoms, such as disorientation and hallucinations, can develop. Treatment to manage the disease is more effective in the earlier stages, but detection is difficult since mild symptoms are often attributed to the normal aging process.
O’Connell and Adams specialize in the complex ways that Alzheimer’s effects how people speak. Using AI, their mathematical model analyzes 15 million data points every minute, focusing on certain features of speech such as pitch, pauses and elongation of words. It also pays attention to how the vibrations of vocal cords change in different stages of the disease.
To create their model, the team used a type of machine learning called deep neural nets, which looks at multiple layers of data - in this case, the multiple features of a person’s speech patterns.
“Deep neural nets allow us to look at much, much larger data sets built out of millions of elements,” O’Connell explained. “Through machine learning and AI, we’ve identified features that are very sensitive to an Alzheimer’s patient versus [people without the disease] and also very sensitive to mild cognitive impairment, early stage and moderate Alzheimer's.” Based on their learnings, Canary is able to classify the disease stage very quickly, O’Connell said.
“When we’re listening to sublanguage elements, we’re really analyzing the direct result of changes in the brain in the physical body,” O’Connell said. “The brain controls your vocal cords: how fast they vibrate, the expansion of them, the contraction.” These factors, along with where people put their tongues when talking, function subconsciously and result in subtle changes in the sounds of speech.
Further testing is needed
In an initial trial, Canary analyzed speech recordings from phone calls to a large U.S. health insurer. They looked at the audio recordings of 651 policyholders who had early stage Alzheimer’s and 1018 who did not have the condition, aiming for a representative sample of age, gender and race. They used this data to create their first diagnostic model and found that it was 96 percent accurate in identifying Alzheimer’s.
Christian Herff, an assistant professor of neuroscience at Maastricht University in the Netherlands, praised this approach while adding that further testing is needed to assess its effectiveness.
“I think the general idea of identifying increased risk for cognitive impairment based on speech characteristics is very feasible, particularly when change in a user’s voice is monitored, for example, by recording speech every year,” Herff said. He noted that this can only be a first indication, not a full diagnosis. The accuracy still needs to be validated in studies that follows individuals over a period of time, he said.
Toby Walsh, a professor of artificial intelligence at the University of New South Wales, also thinks Canary’s tool has potential but highlights that Canary could diagnose some people who don’t really have the disease. “This is an interesting and promising application of AI,” he said, “but these tools need to be used carefully. Imagine the anxiety of being misdiagnosed with Alzheimer’s.”
As with many other AI tools, privacy and bias are additional issues to monitor closely, Walsh said.
Other languages
A related issue is that not everyone is fluent in English. Mahnaz Arvaneh, a senior lecturer in automatic control and systems engineering at the University of Sheffield, said this could be a blind spot.
“The system may not be very accurate for those who have English as their second language as their speaking patterns would be different, and any issue might be because of language deficiency rather than cognitive issues,” Arvaneh said.
The team is expanding to multiple languages starting with Japanese and Spanish. The elements of the model that make up the algorithm are very similar, but they need to be validated and retrained in a different language, which will require access to more data.
Recently, Canary analyzed the phone calls of 233 Japanese patients who had mild cognitive impairment and 704 healthy people. Using an English model they were able to identify the Japanese patients who had mild cognitive impairment with 78 percent accuracy. They also developed a model in Japanese that was 45 percent accurate, and they’re continuing to train it with more data.
The future
Canary is using their model to look at other diseases like Huntington’s and Parkinson’s. They’re also collaborating with pharmaceuticals to validate potential therapies for Alzheimer’s. By looking at speech patterns over time, Canary can get an indication of how well these drugs are working.
Dave Arnold and his wife dance at his nephew’s wedding in Rochester, New York, ten years ago, before his Alzheimer's diagnosis.
Dave Arnold
Ultimately, they want to integrate their tool into everyday life. “We want it to be used in a smartphone, or a teleconference call so that individuals could be examined in their home,” O’Connell said. “We could follow them over time and work with clinical teams and hospitals to improve the evaluation of patients and contribute towards an accurate diagnosis.”
Arnold, the patient with early stage Alzheimer’s, sees great promise. “The process of getting a diagnosis is already filled with so much anxiety,” he said. “Anything that can be done to make it easier and less stressful would be a good thing, as long as it’s proven accurate.”