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.”
Today's podcast episode features Doug Drysdale, CEO of Cybin, a company that is leading innovations in psilocybin, mushrooms that may help people with anxiety and depression.
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These mushrooms have been used for religious, spiritual and medicinal purposes for thousands of years, but only in the past several decades have scientists brought psychedelics into the lab to enhance them and maximize their therapeutic value.
Today’s podcast guest, Doug Drysdale, is doing important work to lead this effort. Drysdale is the CEO of a company called Cybin that has figured out how to make psilocybin more potent, so it can be administered in smaller doses without side effects.
The natural form of psilocybin has been studied increasingly in the realm of mental health. Taking doses of these mushrooms appears to help people with anxiety and depression by spurring the development of connections in the brain, an example of neuroplasticity. The process basically shifts the adult brain from being fairly rigid like dried clay into a malleable substance like warm wax - the state of change that's constantly underway in the developing brains of children.
Neuroplasticity in adults seems to unlock some of our default ways of of thinking, the habitual thought patterns that’ve been associated with various mental health problems. Some promising research suggests that psilocybin causes a reset of sorts. It makes way for new, healthier thought patterns.
So what is Drysdale’s secret weapon to bring even more therapeutic value to psilocybin? It’s a process called deuteration. It focuses on the hydrogen atoms in psilocybin. These atoms are very light and don’t stick very well to carbon, which is another atom in psilocybin. As a result, our bodies can easily breaks down the bonds between the hydrogen and carbon atoms. For many people, that means psilocybin gets cleared from the body too quickly, before it can have a therapeutic benefit.
In deuteration, scientists do something simple but ingenious: they replace the hydrogen atoms with a molecule called deuterium. It’s twice as heavy as hydrogen and forms tighter bonds with the carbon. Because these pairs are so rock-steady, they slow down the rate at which psilocybin is metabolized, so it has more sustained effects on our brains.
Cybin isn’t Drysdale’s first go around at this - far from it. He has over 30 years of experience in the healthcare sector. During this time he’s raised around $4 billion of both public and private capital, and has been named Ernst and Young Entrepreneur of the Year. Before Cybin, he was the founding CEO of a pharmaceutical company called Alvogen, leading it from inception to around $500 million in revenues, across 35 countries. Drysdale has also been the head of mergers and acquisitions at Actavis Group, leading 15 corporate acquisitions across three continents.
In this episode, Drysdale walks us through the promising research of his current company, Cybin, and the different therapies he’s developing for anxiety and depression based not just on psilocybin but another psychedelic compound found in plants called DMT. He explains how they seem to have such powerful effects on the brain, as well as the potential for psychedelics to eventually support other use cases, including helping us strive toward higher levels of well-being. He goes on to discuss his views on mindfulness and lifestyle factors - such as optimal nutrition - that could help bring out hte best in psychedelics.
Show links:
Doug Drysdale full bio
Doug Drysdale twitter
Cybin website
Cybin development pipeline
Cybin's promising phase 2 research on depression
Johns Hopkins psychedelics research and psilocybin research
Mets owner Steve Cohen invests in psychedelic therapies
Doug Drysdale, CEO of Cybin
Immune cells battle an infection.
Measuring immune resilience
The researchers measured immune resilience in two ways. The first is based on the relative quantities of two types of immune cells, CD4+ T cells and CD8+ T cells. CD4+ T cells coordinate the immune system’s response to pathogens and are often used to measure immune health (with higher levels typically suggesting a stronger immune system). However, in 2021, the researchers found that a low level of CD8+ T cells (which are responsible for killing damaged or infected cells) is also an important indicator of immune health. In fact, patients with high levels of CD4+ T cells and low levels of CD8+ T cells during SARS-CoV-2 and HIV infection were the least likely to develop severe COVID and AIDS.
Individuals with optimal levels of immune resilience were more likely to live longer.
In the same 2021 study, the researchers identified a second measure of immune resilience that involves two gene expression signatures correlated with an infected person’s risk of death. One of the signatures was linked to a higher risk of death; it includes genes related to inflammation — an essential process for jumpstarting the immune system but one that can cause considerable damage if left unbridled. The other signature was linked to a greater chance of survival; it includes genes related to keeping inflammation in check. These genes help the immune system mount a balanced immune response during infection and taper down the response after the threat is gone. The researchers found that participants who expressed the optimal combination of genes lived longer.
Immune resilience and longevity
The researchers assessed levels of immune resilience in nearly 50,000 participants of different ages and with various types of challenges to their immune systems, including acute infections, chronic diseases, and cancers. Their evaluation demonstrated that individuals with optimal levels of immune resilience were more likely to live longer, resist HIV and influenza infections, resist recurrence of skin cancer after kidney transplant, survive COVID infection, and survive sepsis.
However, a person’s immune resilience fluctuates all the time. Study participants who had optimal immune resilience before common symptomatic viral infections like a cold or the flu experienced a shift in their gene expression to poor immune resilience within 48 hours of symptom onset. As these people recovered from their infection, many gradually returned to the more favorable gene expression levels they had before. However, nearly 30% who once had optimal immune resilience did not fully regain that survival-associated profile by the end of the cold and flu season, even though they had recovered from their illness.
Intriguingly, some people who are 90+ years old still have optimal immune resilience, suggesting that these individuals’ immune systems have an exceptional capacity to control inflammation and rapidly restore proper immune balance.
This could suggest that the recovery phase varies among people and diseases. For example, young female sex workers who had many clients and did not use condoms — and thus were repeatedly exposed to sexually transmitted pathogens — had very low immune resilience. However, most of the sex workers who began reducing their exposure to sexually transmitted pathogens by using condoms and decreasing their number of sex partners experienced an improvement in immune resilience over the next 10 years.
Immune resilience and aging
The researchers found that the proportion of people with optimal immune resilience tended to be highest among the young and lowest among the elderly. The researchers suggest that, as people age, they are exposed to increasingly more health conditions (acute infections, chronic diseases, cancers, etc.) which challenge their immune systems to undergo a “respond-and-recover” cycle. During the response phase, CD8+ T cells and inflammatory gene expression increase, and during the recovery phase, they go back down.
However, over a lifetime of repeated challenges, the immune system is slower to recover, altering a person’s immune resilience. Intriguingly, some people who are 90+ years old still have optimal immune resilience, suggesting that these individuals’ immune systems have an exceptional capacity to control inflammation and rapidly restore proper immune balance despite the many respond-and-recover cycles that their immune systems have faced.
Public health ramifications could be significant. Immune cell and gene expression profile assessments are relatively simple to conduct, and being able to determine a person’s immune resilience can help identify whether someone is at greater risk for developing diseases, how they will respond to treatment, and whether, as well as to what extent, they will recover.
