There’s a growing need to slow down the aging process. The world’s population is getting older and, according to one estimate, 80 million Americans will be 65 or older by 2040. As we age, the risk of many chronic diseases goes up, from cancer to heart disease to Alzheimer’s.
BioAge Labs, a company based in California, is using genetic data to help people stay healthy for longer. CEO Kristen Fortney was inspired by the genetics of people who live long lives and resist many age-related diseases. In 2015, she started BioAge to study them and develop drug therapies based on the company’s learnings.
The team works with special biobanks that have been collecting blood samples and health data from individuals for up to 45 years. Using artificial intelligence, BioAge is able to find the distinctive molecular features that distinguish those who have healthy longevity from those who don’t.
In December 2022, BioAge published findings on a drug that worked to prevent muscular atrophy, or the loss of muscle strength and mass, in older people. Much of the research on aging has been in worms and mice, but BioAge is focused on human data, Fortney says. “This boosts our chances of developing drugs that will be safe and effective in human patients.”
How it works
With assistance from AI, BioAge measures more than 100,000 molecules in each blood sample, looking at proteins, RNA and metabolites, or small molecules that are produced through chemical processes. The company uses many techniques to identify these molecules, some of which convert the molecules into charged atoms and then separating them according to their weight and charge. The resulting data is very complex, with many thousands of data points from patients being followed over the decades.
BioAge validates its targets by examining whether a pathway going awry is actually linked to the development of diseases, based on the company’s analysis of biobank health records and blood samples. The team uses AI and machine learning to identify these pathways, and the key proteins in the unhealthy pathways become their main drug targets. “The approach taken by BioAge is an excellent example of how we can harness the power of big data and advances in AI technology to identify new drugs and therapeutic targets,” says Lorna Harries, a professor of molecular genetics at the University of Exeter Medical School.
Martin Borch Jensen is the founder of Gordian Biotechnology, a company focused on using gene therapy to treat aging. He says BioAge’s use of AI allows them to speed up the process of finding promising drug candidates. However, it remains a challenge to separate pathologies from aspects of the natural aging process that aren’t necessarily bad. “Some of the changes are likely protective responses to things going wrong,” Jensen says. “Their data doesn’t…distinguish that so they’ll need to validate and be clever.”
Developing a drug for muscle loss
BioAge decided to focus on muscular atrophy because it affects many elderly people, making it difficult to perform everyday activities and increasing the risk of falls. Using the biobank samples, the team modeled different pathways that looked like they could improve muscle health. They found that people who had faster walking speeds, better grip strength and lived longer had higher levels of a protein called apelin.
Apelin is a peptide, or a small protein, that circulates in the blood. It is involved in the process by which exercise increases and preserves muscle mass. BioAge wondered if they could prevent muscular atrophy by increasing the amount of signaling in the apelin pathway. Instead of the long process of designing a drug, they decided to repurpose an existing drug made by another biotech company. This company, called Amgen, had explored the drug as a way to treat heart failure. It didn’t end up working for that purpose, but BioAge took note that the drug did seem to activate the apelin pathway.
BioAge tested its new, repurposed drug, BGE-105, and, in a phase 1 clinical trial, it protected subjects from getting muscular atrophy compared to a placebo group that didn’t receive the drug. Healthy volunteers over age 65 received infusions of the drug during 10 days spent in bed, as if they were on bed rest while recovering from an illness or injury; the elderly are especially vulnerable to muscle loss in this situation. The 11 people taking BGE-105 showed a 100 percent improvement in thigh circumference compared to 10 people taking the placebo. Ultrasound observations also revealed that the group taking the durg had enhanced muscle quality and a 73 percent increase in muscle thickness. One volunteer taking BGE-105 did have muscle loss compared to the the placebo group.
Heather Whitson, the director of the Duke University Centre for the study of aging and human development, says that, overall, the results are encouraging. “The clinical findings so far support the premise that AI can help us sort through enormous amounts of data and identify the most promising points for beneficial interventions.”
More studies are needed to find out which patients benefit the most and whether there are side effects. “I think further studies will answer more questions,” Whitson says, noting that BGE-105 was designed to enhance only one aspect of physiology associated with exercise, muscle strength. But exercise itself has many other benefits on mood, sleep, bones and glucose metabolism. “We don’t know whether BGE-105 will impact these other outcomes,” she says.
BioAge is planning phase 2 trials for muscular atrophy in patients with obesity and those who have been hospitalized in an intensive care unit. Using the data from biobanks, they’ve also developed another drug, BGE-100, to treat chronic inflammation in the brain, a condition that can worsen with age and contributes to neurodegenerative diseases. The team is currently testing the drug in animals to assess its effects and find the right dose.
BioAge envisions that its drugs will have broader implications for health than treating any one specific disease. “Ultimately, we hope to pioneer a paradigm shift in healthcare, from treatment to prevention, by targeting the root causes of aging itself,” Fortney says. “We foresee a future where healthy longevity is within reach for all.”
Martin Taylor was only 32 when he was diagnosed with Parkinson's, a disease that causes tremors, stiff muscles and slow physical movement - symptoms that steadily get worse as time goes on.
“It's horrible having Parkinson's,” says Taylor, a data analyst, now 41. “It limits my ability to be the dad and husband that I want to be in many cruel and debilitating ways.”
Today, more than 10 million people worldwide live with Parkinson's. Most are diagnosed when they're considerably older than Taylor, after age 60. Although recent research has called into question certain aspects of the disease’s origins, Parkinson’s eventually kills the nerve cells in the brain that produce dopamine, a signaling chemical that carries messages around the body to control movement. Many patients have lost 60 to 80 percent of these cells by the time they are diagnosed.
For years, there's been little improvement in the standard treatment. Patients are typically given the drug levodopa, a chemical that's absorbed by the brain’s nerve cells, or neurons, and converted into dopamine. This drug addresses the symptoms but has no impact on the course of the disease as patients continue to lose dopamine producing neurons. Eventually, the treatment stops working effectively.
BlueRock Therapeutics, a cell therapy company based in Massachusetts, is taking a different approach by focusing on the use of stem cells, which can divide into and generate new specialized cells. The company makes the dopamine-producing cells that patients have lost and inserts these cells into patients' brains. “We have a disease with a high unmet need,” says Ahmed Enayetallah, the senior vice president and head of development at BlueRock. “We know [which] cells…are lost to the disease, and we can make them. So it really came together to use stem cells in Parkinson's.”
In a phase 1 research trial announced late last month, patients reported that their symptoms had improved after a year of treatment. Brain scans also showed an increased number of neurons generating dopamine in patients’ brains.
Increases in dopamine signals
The recent phase 1 trial focused on deploying BlueRock’s cell therapy, called bemdaneprocel, to treat 12 patients suffering from Parkinson’s. The team developed the new nerve cells and implanted them into specific locations on each side of the patient's brain through two small holes in the skull made by a neurosurgeon. “We implant cells into the places in the brain where we think they have the potential to reform the neural networks that are lost to Parkinson's disease,” Enayetallah says. The goal is to restore motor function to patients over the long-term.
Five patients were given a relatively low dose of cells while seven got higher doses. Specialized brain scans showed evidence that the transplanted cells had survived, increasing the overall number of dopamine producing cells. The team compared the baseline number of these cells before surgery to the levels one year later. “The scans tell us there is evidence of increased dopamine signals in the part of the brain affected by Parkinson's,” Enayetallah says. “Normally you’d expect the signal to go down in untreated Parkinson’s patients.”
"I think it has a real chance to reverse motor symptoms, essentially replacing a missing part," says Tilo Kunath, a professor of regenerative neurobiology at the University of Edinburgh.
The team also asked patients to use a specific type of home diary to log the times when symptoms were well controlled and when they prevented normal activity. After a year of treatment, patients taking the higher dose reported symptoms were under control for an average of 2.16 hours per day above their baselines. At the smaller dose, these improvements were significantly lower, 0.72 hours per day. The higher-dose patients reported a corresponding decrease in the amount of time when symptoms were uncontrolled, by an average of 1.91 hours, compared to 0.75 hours for the lower dose. The trial was safe, and patients tolerated the year of immunosuppression needed to make sure their bodies could handle the foreign cells.
Claire Bale, the associate director of research at Parkinson's U.K., sees the promise of BlueRock's approach, while noting the need for more research on a possible placebo effect. The trial participants knew they were getting the active treatment, and placebo effects are known to be a potential factor in Parkinson’s research. Even so, “The results indicate that this therapy produces improvements in symptoms for Parkinson's, which is very encouraging,” Bale says.
Tilo Kunath, a professor of regenerative neurobiology at the University of Edinburgh, also finds the results intriguing. “I think it's excellent,” he says. “I think it has a real chance to reverse motor symptoms, essentially replacing a missing part.” However, it could take time for this therapy to become widely available, Kunath says, and patients in the late stages of the disease may not benefit as much. “Data from cell transplantation with fetal tissue in the 1980s and 90s show that cells did not survive well and release dopamine in these [late-stage] patients.”
Searching for the right approach
There's a long history of using cell therapy as a treatment for Parkinson's. About four decades ago, scientists at the University of Lund in Sweden developed a method in which they transferred parts of fetal brain tissue to patients with Parkinson's so that their nerve cells would produce dopamine. Many benefited, and some were able to stop their medication. However, the use of fetal tissue was highly controversial at that time, and the tissues were difficult to obtain. Later trials in the U.S. showed that people benefited only if a significant amount of the tissue was used, and several patients experienced side effects. Eventually, the work lost momentum.
“Like many in the community, I'm aware of the long history of cell therapy,” says Taylor, the patient living with Parkinson's. “They've long had that cure over the horizon.”
In 2000, Lorenz Studer led a team at the Memorial Sloan Kettering Centre, in New York, to find the chemical signals needed to get stem cells to differentiate into cells that release dopamine. Back then, the team managed to make cells that produced some dopamine, but they led to only limited improvements in animals. About a decade later, in 2011, Studer and his team found the specific signals needed to guide embryonic cells to become the right kind of dopamine producing cells. Their experiments in mice, rats and monkeys showed that their implanted cells had a significant impact, restoring lost movement.
Studer then co-founded BlueRock Therapeutics in 2016. Forming the most effective stem cells has been one of the biggest challenges, says Enayetallah, the BlueRock VP. “It's taken a lot of effort and investment to manufacture and make the cells at the right scale under the right conditions.” The team is now using cells that were first isolated in 1998 at the University of Wisconsin, a major advantage because they’re available in a virtually unlimited supply.
Other efforts underway
In the past several years, University of Lund researchers have begun to collaborate with the University of Cambridge on a project to use embryonic stem cells, similar to BlueRock’s approach. They began clinical trials this year.
A company in Japan called Sumitomo is using a different strategy; instead of stem cells from embryos, they’re reprogramming adults' blood or skin cells into induced pluripotent stem cells - meaning they can turn into any cell type - and then directing them into dopamine producing neurons. Although Sumitomo started clinical trials earlier than BlueRock, they haven’t yet revealed any results.
“It's a rapidly evolving field,” says Emma Lane, a pharmacologist at the University of Cardiff who researches clinical interventions for Parkinson’s. “But BlueRock’s trial is the first full phase 1 trial to report such positive findings with stem cell based therapies.” The company’s upcoming phase 2 research will be critical to show how effectively the therapy can improve disease symptoms, she added.
The cure over the horizon
BlueRock will continue to look at data from patients in the phase 1 trial to monitor the treatment’s effects over a two-year period. Meanwhile, the team is planning the phase 2 trial with more participants, including a placebo group.
For patients with Parkinson’s like Martin Taylor, the therapy offers some hope, though Taylor recognizes that more research is needed.
“Like many in the community, I'm aware of the long history of cell therapy,” he says. “They've long had that cure over the horizon.” His expectations are somewhat guarded, he says, but, “it's certainly positive to see…movement in the field again.”
"If we can demonstrate what we’re seeing today in a more robust study, that would be great,” Enayetallah says. “At the end of the day, we want to address that unmet need in a field that's been waiting for a long time.”
Editor's note: The company featured in this piece, BlueRock Therapeutics, is a portfolio company of Leaps by Bayer, which is a sponsor of Leaps.org. BlueRock was acquired by Bayer Pharmaceuticals in 2019. Leaps by Bayer and other sponsors have never exerted influence over Leaps.org content or contributors.
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.
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.
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.
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.”