A decellularized small porcine liver.
Jennifer Cisneros was 18 years old, commuting to college from her family's home outside Annapolis, Maryland, when she came down with what she thought was the flu. Over the following weeks, however, her fatigue and nausea worsened, and her weight began to plummet. Alarmed, her mother took her to see a pediatrician. "When I came back with the urine cup, it was orange," Cisneros recalls. "He was like, 'Oh, my God. I've got to send you for blood work.'"
"Eventually, we'll be better off than with a human organ."
Further tests showed that her kidneys were failing, and at Johns Hopkins Hospital, a biopsy revealed the cause: Goodpasture syndrome (GPS), a rare autoimmune disease that attacks the kidneys or lungs. Cisneros was put on dialysis to filter out the waste products that her body could no longer process, and given chemotherapy and steroids to suppress her haywire immune system.
The treatment drove her GPS into remission, but her kidneys were beyond saving. At 19, Cisneros received a transplant, with her mother as donor. Soon, she'd recovered enough to return to school; she did some traveling, and even took up skydiving and parasailing. Then, after less than two years, rejection set in, and the kidney had to be removed.
She went back on dialysis until she was 26, when a stranger learned of her plight and volunteered to donate. That kidney lasted four years, but gave out after a viral infection. Since 2015, Cisneros—now 32, and working as an office administrator between thrice-weekly blood-filtering sessions—has been waiting for a replacement.
She's got plenty of company. About 116,000 people in the United States currently need organ transplants, but fewer than 35,000 organs become available every year. On average, 20 people on the waiting list die each day. And despite repeated campaigns to boost donorship, the gap shows no sign of narrowing.
"This is going to revolutionize medicine, in ways we probably can't yet appreciate."
For decades, doctors and scientists have envisioned a radical solution to the shortage: harvesting other species for spare parts. Xenotransplantation, as the practice is known, could provide an unlimited supply of lifesaving organs for patients like Cisneros. Those organs, moreover, could be altered by genetic engineering or other methods to reduce the danger of rejection—and thus to eliminate the need for immunosuppressive drugs, whose potential side effects include infections, diabetes, and cancer. "Eventually, we'll be better off than with a human organ," says David Cooper, MD, PhD, co-director of the xenotransplant program at the University of Alabama School of Medicine. "This is going to revolutionize medicine, in ways we probably can't yet appreciate."
Recently, progress toward that revolution has accelerated sharply. The cascade of advances began in April 2016, when researchers at the National Heart, Lung, and Blood Institute (NHLBI) reported keeping pig hearts beating in the abdomens of five baboons for a record-breaking mean of 433 days, with one lasting more than two-and-a-half years. Then a team at Emory University announced that a pig kidney sustained a rhesus monkey for 435 days before being rejected, nearly doubling the previous record. At the University of Munich, in Germany, researchers doubled the record for a life-sustaining pig heart transplant in a baboon (replacing the animal's own heart) to 90 days. Investigators at the Salk Institute and the University of California, Davis, declared that they'd grown tissue in pig embryos using human stem cells—a first step toward cultivating personalized replacement organs. The list goes on.
Such breakthroughs, along with a surge of cash from biotech investors, have propelled a wave of bullish media coverage. Yet this isn't the first time that xenotransplantation has been touted as the next big thing. Twenty years ago, the field seemed poised to overcome its final hurdles, only to encounter a setback from which it is just now recovering.
Which raises a question: Is the current excitement justified? Or is the hype again outrunning the science?
A History of Setbacks
The idea behind xenotransplantation dates back at least as far as the 17th century, when French physician Jean-Baptiste Denys tapped the veins of sheep and cows to perform the first documented human blood transfusions. (The practice was banned after two of the four patients died, probably from an immune reaction.) In the 19th century, surgeons began transplanting corneas from pigs and other animals into humans, and using skin xenografts to aid in wound healing; despite claims of miraculous cures, medical historians believe those efforts were mostly futile. In the 1920s and '30s, thousands of men sought renewed vigor through testicular implants from monkeys or goats, but the fad collapsed after studies showed the effects to be imaginary.
Research shut down when scientists discovered a virus in pig DNA that could infect human cells.
After the first successful human organ transplant in 1954—of a kidney, passed between identical twin sisters—the limited supply of donor organs brought a resurgence of interest in animal sources. Attention focused on nonhuman primates, our species' closest evolutionary relatives. At Tulane University, surgeon Keith Reemstma performed the first chimpanzee-to-human kidney transplants in 1963 and '64. Although one of the 13 patients lived for nine months, the rest died within a few weeks due to organ rejection or infections. Other surgeons attempted liver and heart xenotransplants, with similar results. Even the advent of the first immunosuppressant drug, cyclosporine, in 1983, did little to improve survival rates.
In the 1980s, Cooper—a pioneering heart transplant surgeon who'd embraced the dream of xenotransplantation—began arguing that apes and monkeys might not be the best donor animals after all. "First of all, there's not enough of them," he explains. "They breed in ones and twos, and take years to grow to full size. Even then, their hearts aren't big enough for a 70-kg. patient." Pigs, he suggested, would be a more practical alternative. But when he tried transplanting pig organs into nonhuman primates (as surrogates for human recipients), they were rejected within minutes.
In 1992, Cooper's team identified a sugar on the surface of porcine cells, called alpha-1,3-galactose (a-gal), as the main target for the immune system's attack. By then, the first genetically modified pigs had appeared, and biotech companies—led by the Swiss-based pharma giant Novartis—began pouring millions of dollars into developing one whose organs could elude or resist the human body's defenses.
Disaster struck five years later, when scientists reported that a virus whose genetic code was written into pig DNA could infect human cells in lab experiments. Although there was no evidence that the virus, known as PERV (for porcine endogenous retrovirus) could cause disease in people, the discovery stirred fears that xenotransplants might unleash a deadly epidemic. Facing scrutiny from government regulators and protests from anti-GMO and animal-rights activists, Novartis "pulled out completely," Cooper recalls. "They slaughtered all their pigs and closed down their research facility." Competitors soon followed suit.
The riddles surrounding animal-to-human transplants are far from fully solved.
A New Chapter – With New Questions
Yet xenotransplantation's visionaries labored on, aided by advances in genetic engineering and immunosuppression, as well as in the scientific understanding of rejection. In 2003, a team led by Cooper's longtime colleague David Sachs, at Harvard Medical School, developed a pig lacking the gene for a-gal; over the next few years, other scientists knocked out genes expressing two more problematic sugars. In 2013, Muhammad Mohiuddin, then chief of the transplantation section at the NHLBI, further modified a group of triple-knockout pigs, adding genes that code for two human proteins: one that shields cells from attack by an immune mechanism known as the complement system; another that prevents harmful coagulation. (It was those pigs whose hearts recently broke survival records when transplanted into baboon bellies. Mohiuddin has since become director of xenoheart transplantation at the University of Maryland's new Center for Cardiac Xenotransplantation Research.) And in August 2017, researchers at Harvard Medical School, led by George Church and Luhan Yang, announced that they'd used CRISPR-cas9—an ultra-efficient new gene-editing technique—to disable 62 PERV genes in fetal pig cells, from which they then created cloned embryos. Of the 37 piglets born from this experiment, none showed any trace of the virus.
Still, the riddles surrounding animal-to-human transplants are far from fully solved. One open question is what further genetic manipulations will be necessary to eliminate all rejection. "No one is so naïve as to think, 'Oh, we know all the genes—let's put them in and we are done,'" biologist Sean Stevens, another leading researcher, told the The New York Times. "It's an iterative process, and no one that I know can say whether we will do two, or five, or 100 iterations." Adding traits can be dangerous as well; pigs engineered to express multiple anticoagulation proteins, for example, often die of bleeding disorders. "We're still finding out how many you can do, and what levels are acceptable," says Cooper.
Another question is whether PERV really needs to be disabled. Cooper and some of his colleagues note that pig tissue has long been used for various purposes, such as artificial heart valves and wound-repair products, without incident; requiring the virus to be eliminated, they argue, will unnecessarily slow progress toward creating viable xenotransplant organs and the animals that can provide them. Others disagree. "You cannot do anything with pig organs if you do not remove them," insists bioethicist Jeantine Lunshof, who works with Church and Yang at Harvard. "The risk is simply too big."
"We've removed the cells, so we don't have to worry about latent viruses."
Meanwhile, over the past decade, other approaches to xenotransplantation have emerged. One is interspecies blastocyst complementation, which could produce organs genetically identical to the recipient's tissues. In this method, genes that produce a particular organ are knocked out in the donor animal's embryo. The embryo is then injected with pluripotent stem cells made from the tissue of the intended recipient. The stem cells move in to fill the void, creating a functioning organ. This technique has been used to create mouse pancreases in rats, which were then successfully transplanted into mice. But the human-pig "chimeras" recently created by scientists were destroyed after 28 days, and no one plans to bring such an embryo to term anytime soon. "The problem is that cells don't stay put; they move around," explains Father Kevin FitzGerald, a bioethicist at Georgetown University. "If human cells wind up in a pig's brain, that leads to a really interesting conundrum. What if it's self-aware? Are you going to kill it?"
Much further along, and less ethically fraught, is a technique in which decellularized pig organs act as a scaffold for human cells. A Minnesota-based company called Miromatrix Medical is working with Mayo Clinic researchers to develop this method. First, a mild detergent is pumped through the organ, washing away all cellular material. The remaining structure, composed mainly of collagen, is placed in a bioreactor, where it's seeded with human cells. In theory, each type of cell that normally populates the organ will migrate to its proper place (a process that naturally occurs during fetal development, though it remains poorly understood). One potential advantage of this system is that it doesn't require genetically modified pigs; nor will the animals have to be raised under controlled conditions to avoid exposure to transmissible pathogens. Instead, the organs can be collected from ordinary slaughterhouses.
Recellularized livers in bioreactors
(Courtesy of Miromatrix)
"We've removed the cells, so we don't have to worry about latent viruses," explains CEO Jeff Ross, who describes his future product as a bioengineered human organ rather than a xeno-organ. That makes PERV a nonissue. To shorten the pathway to approval by the Food and Drug Administration, the replacement cells will initially come from human organs not suitable for transplant. But eventually, they'll be taken from the recipient (as in blastocyst complementation), which should eliminate the need for immunosuppression.
Clinical trials in xenotransplantation may begin as early as 2020.
Miromatrix plans to offer livers first, followed by kidneys, hearts, and eventually lungs and pancreases. The company recently succeeded in seeding several decellularized pig livers with human and porcine endothelial cells, which flocked obediently to the blood vessels. Transplanted into young pigs, the organs showed unimpaired circulation, with no sign of clotting. The next step is to feed all four liver cell types back into decellularized livers, and see if the transplanted organs will keep recipient pigs alive.
Ross hopes to launch clinical trials by 2020, and several other groups (including Cooper's, which plans to start with kidneys) envision a similar timeline. Investors seem to share their confidence. The biggest backer of xenotransplantation efforts is United Therapeutics, whose founder and co-CEO, Martine Rothblatt, has a daughter with a lung condition that may someday require a transplant; since 2011, the biotech firm has poured at least $100 million into companies pursuing such technologies, while supporting research by Cooper, Mohiuddin, and other leaders in the field. Church and Yang, at Harvard, have formed their own company, eGenesis, bringing in a reported $40 million in funding; Miromatrix has raised a comparable amount.
It's impossible to predict who will win the xenotransplantation race, or whether some new obstacle will stop the competition in its tracks. But Jennifer Cisneros is rooting for all the contestants. "These technologies could save my life," she says. If she hasn't found another kidney before trials begin, she has just one request: "Sign me up."
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.”