In an initial study, Canary analyzed speech recordings with AI and identified early stage Alzheimer’s with 96 percent accuracy.
Dave Arnold retired in his 60s and began spending time volunteering in local schools. But then he started misplacing items, forgetting appointments and losing his sense of direction. Eventually he was diagnosed with early stage Alzheimer’s.
“Hearing the diagnosis made me very emotional and tearful,” he said. “I immediately thought of all my mom had experienced.” His mother suffered with the condition for years before passing away. Over the last year, Arnold has worked for the Alzheimer’s Association as one of its early stage advisors, sharing his insights to help others in the initial stages of the disease.
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.”
Many women want non-hormonal birth control. A 22-year-old's findings were used to launch a company that could, within the decade, bring a new kind of contraceptive to the marketplace.
Now a scientist with NextVivo, Shrestha is not directly involved in the development of the contraceptive that is based on her research. But, back in 2016 when she was going through her own problems with hormonal contraceptives, she “was very personally invested” in her research project, Shrestha says. She was coping with a long list of negative effects from an implanted hormonal IUD. According to the Mayo Clinic, those can include severe pelvic pain, headaches, acute acne, breast tenderness, irregular bleeding and mood swings. After a year, she had the IUD removed, but it took another full year before all the side effects finally subsided; she also watched her sister suffer the “same tribulations” after trying a hormonal IUD, she says.
For contraceptive use either daily or monthly, Shrestha says, “You want the antibody to be very potent and also cheap.” That was her goal when she launched her study.
Shrestha unshelved antibody research that had been sitting idle for decades. It was in the late 80s that scientists in Japan first tried to develop anti-sperm antibodies for contraceptive use. But, 35 years ago, “Antibody production had not been streamlined as it is now, so antibodies were very expensive,” Shrestha explains. So, they shifted away from birth control, opting to focus on developing antibodies for vaccines.
Over the course of the last three decades, different teams of researchers have been working to make the antibody more effective, bringing the cost down, though it’s still expensive, according to Shrestha. For contraceptive use either daily or monthly, she says, “You want the antibody to be very potent and also cheap.” That was her goal when she launched her study.
The problem
The problem with contraceptives for women, Shrestha says, is that all but a few of them are hormone-based or have other negative side effects. In fact, some studies and reports show that millions of women risk unintended pregnancy because of medical contraindications with hormone-based contraceptives or to avoid the risks and side effects. While there are about a dozen contraceptive choices for women, there are two for men: the condom, considered 98% effective if used correctly, and vasectomy, 99% effective. Neither of these choices are hormone-based.
On the non-hormonal side for women, there is the diaphragm which is considered only 87 percent effective. It works better with the addition of spermicides — Nonoxynol-9, or N-9 — however, they are detergents; they not only kill the sperm, they also erode the vaginal epithelium. And, there’s the non-hormonal IUD which is 99% effective. However, the IUD needs to be inserted by a medical professional, and it has a number of negative side effects, including painful cramping at a higher frequency and extremely heavy or “abnormal” and unpredictable menstrual flows.
The hormonal version of the IUD, also considered 99% effective, is the one Shrestha used which caused her two years of pain. Of course, there’s the pill, which needs to be taken daily, and the birth control ring which is worn 24/7. Both cause side effects similar to the other hormonal contraceptives on the market. The ring is considered 93% effective mostly because of user error; the pill is considered 99% effective if taken correctly.
“That’s where we saw this opening or gap for women. We want a safe, non-hormonal contraceptive,” Shrestha says. Compounding the lack of good choices, is poor access to quality sex education and family planning information, according to the non-profit Urban Institute. A focus group survey suggested that the sex education women received “often lacked substance, leaving them feeling unprepared to make smart decisions about their sexual health and safety,” wrote the authors of the Urban Institute report. In fact, nearly half (45%, or 2.8 million) of the pregnancies that occur each year in the US are unintended, reports the Guttmacher Institute. Globally the numbers are similar. According to a new report by the United Nations, each year there are 121 million unintended pregnancies, worldwide.
The science
The early work on antibodies as a contraceptive had been inspired by women with infertility. It turns out that 9 to 12 percent of women who are treated for infertility have antibodies that develop naturally and work against sperm. Shrestha was encouraged that the antibodies were specific to the target — sperm — and therefore “very safe to use in women.” She aimed to make the antibodies more stable, more effective and less expensive so they could be more easily manufactured.
Since antibodies tend to stick to things that you tell them to stick to, the idea was, basically, to engineer antibodies to stick to sperm so they would stop swimming. Shrestha and her colleagues took the binding arm of an antibody that they’d isolated from an infertile woman. Then, targeting a unique surface antigen present on human sperm, they engineered a panel of antibodies with as many as six to 10 binding arms — “almost like tongs with prongs on the tongs, that bind the sperm,” explains Shrestha. “We decided to add those grabbers on top of it, behind it. So it went from having two prongs to almost 10. And the whole goal was to have so many arms binding the sperm that it clumps it” into a “dollop,” explains Shrestha, who earned a patent on her research.
Suruchi Shrestha works in the lab with a colleague. In 2016, her research on antibodies for birth control was inspired by her own experience with side effects from an implanted hormonal IUD.
UNC - Chapel Hill
The sperm stays right where it met the antibody, never reaching the egg for fertilization. Eventually, and naturally, “Our vaginal system will just flush it out,” Shrestha explains.
“She showed in her early studies that [she] definitely got the sperm immotile, so they didn't move. And that was a really promising start,” says Jasmine Edelstein, a scientist with an expertise in antibody engineering who was not involved in this research. Shrestha’s team at UNC reproduced the effect in the sheep, notes Edelstein, who works at the startup Be Biopharma. In fact, Shrestha’s anti-sperm antibodies that caused the sperm to agglutinate, or clump together, were 99.9% effective when delivered topically to the sheep’s reproductive tracts.
The future
Going forward, Shrestha thinks the ideal approach would be delivering the antibodies through a vaginal ring. “We want to use it at the source of the spark,” Shrestha says, as opposed to less direct methods, such as taking a pill. The ring would dissolve after one month, she explains, “and then you get another one.”
Engineered to have a long shelf life, the anti-sperm antibody ring could be purchased without a prescription, and women could insert it themselves, without a doctor. “That's our hope, so that it is accessible,” Shrestha says. “Anybody can just go and grab it and not worry about pregnancy or unintended pregnancy.”
Her patented research has been licensed by several biotech companies for clinical trials. A number of Shrestha’s co-authors, including her lab advisor, Sam Lai, have launched a company, Mucommune, to continue developing the contraceptives based on these antibodies.
And, results from a small clinical trial run by researchers at Boston University Chobanian & Avedisian School of Medicine show that a dissolvable vaginal film with antibodies was safe when tested on healthy women of reproductive age. That same group of researchers earlier this year received a $7.2 million grant from the National Institute of Health for further research on monoclonal antibody-based contraceptives, which have also been shown to block transmission of viruses, like HIV.
“As the costs come down, this becomes a more realistic option potentially for women,” says Edelstein. “The impact could be tremendous.”