Recent advancements in engineering mean that the first preclinical trials for an artificial kidney could happen as soon as 18 months from now
Like all those whose kidneys have failed, Scott Burton’s life revolves around dialysis. For nearly two decades, Burton has been hooked up (or, since 2020, has hooked himself up at home) to a dialysis machine that performs the job his kidneys normally would. The process is arduous, time-consuming, and expensive. Except for a brief window before his body rejected a kidney transplant, Burton has depended on machines to take the place of his kidneys since he was 12-years-old. His whole life, the 39-year-old says, revolves around dialysis.
“Whenever I try to plan anything, I also have to plan my dialysis,” says Burton says, who works as a freelance videographer and editor. “It’s a full-time job in itself.”
Many of those on dialysis are in line for a kidney transplant that would allow them to trade thrice-weekly dialysis and strict dietary limits for a lifetime of immunosuppressants. Burton’s previous transplant means that his body will likely reject another donated kidney unless it matches perfectly—something he’s not counting on. It’s why he’s enthusiastic about the development of artificial kidneys, small wearable or implantable devices that would do the job of a healthy kidney while giving users like Burton more flexibility for traveling, working, and more.
Still, the devices aren’t ready for testing in humans—yet. But recent advancements in engineering mean that the first preclinical trials for an artificial kidney could happen as soon as 18 months from now, according to Jonathan Himmelfarb, a nephrologist at the University of Washington.
“It would liberate people with kidney failure,” Himmelfarb says.
An engineering marvel
Compared to the heart or the brain, the kidney doesn’t get as much respect from the medical profession, but its job is far more complex. “It does hundreds of different things,” says UCLA’s Ira Kurtz.
Kurtz would know. He’s worked as a nephrologist for 37 years, devoting his career to helping those with kidney disease. While his colleagues in cardiology and endocrinology have seen major advances in the development of artificial hearts and insulin pumps, little has changed for patients on hemodialysis. The machines remain bulky and require large volumes of a liquid called dialysate to remove toxins from a patient’s blood, along with gallons of purified water. A kidney transplant is the next best thing to someone’s own, functioning organ, but with over 600,000 Americans on dialysis and only about 100,000 kidney transplants each year, most of those in kidney failure are stuck on dialysis.
Part of the lack of progress in artificial kidney design is the sheer complexity of the kidney’s job. Each of the 45 different cell types in the kidney do something different.
Part of the lack of progress in artificial kidney design is the sheer complexity of the kidney’s job. To build an artificial heart, Kurtz says, you basically need to engineer a pump. An artificial pancreas needs to balance blood sugar levels with insulin secretion. While neither of these tasks is simple, they are fairly straightforward. The kidney, on the other hand, does more than get rid of waste products like urea and other toxins. Each of the 45 different cell types in the kidney do something different, helping to regulate electrolytes like sodium, potassium, and phosphorous; maintaining blood pressure and water balance; guiding the body’s hormonal and inflammatory responses; and aiding in the formation of red blood cells.
There's been little progress for patients during Ira Kurtz's 37 years as a nephrologist. Artificial kidneys would change that.
UCLA
Dialysis primarily filters waste, and does so well enough to keep someone alive, but it isn’t a true artificial kidney because it doesn’t perform the kidney’s other jobs, according to Kurtz, such as sensing levels of toxins, wastes, and electrolytes in the blood. Due to the size and water requirements of existing dialysis machines, the equipment isn’t portable. Physicians write a prescription for a certain duration of dialysis and assess how well it’s working with semi-regular blood tests. The process of dialysis itself, however, is conducted blind. Doctors can’t tell how much dialysis a patient needs based on kidney values at the time of treatment, says Meera Harhay, a nephrologist at Drexel University in Philadelphia.
But it’s the impact of dialysis on their day-to-day lives that creates the most problems for patients. Only one-quarter of those on dialysis are able to remain employed (compared to 85% of similar-aged adults), and many report a low quality of life. Having more flexibility in life would make a major different to her patients, Harhay says.
“Almost half their week is taken up by the burden of their treatment. It really eats away at their freedom and their ability to do things that add value to their life,” she says.
Art imitates life
The challenge for artificial kidney designers was how to compress the kidney’s natural functions into a portable, wearable, or implantable device that wouldn’t need constant access to gallons of purified and sterilized water. The other universal challenge they faced was ensuring that any part of the artificial kidney that would come in contact with blood was kept germ-free to prevent infection.
As part of last year’s KidneyX Prize, a partnership between the U.S. Department of Health and Human Services and the American Society of Nephrology, inventors were challenged to create prototypes for artificial kidneys. Himmelfarb’s team at the University of Washington’s Center for Dialysis Innovation won the prize by focusing on miniaturizing existing technologies to create a portable dialysis machine. The backpack sized AKTIV device (Ambulatory Kidney to Increase Vitality) will recycle dialysate in a closed loop system that removes urea from blood and uses light-based chemical reactions to convert the urea to nitrogen and carbon dioxide, which allows the dialysate to be recirculated.
Himmelfarb says that the AKTIV can be used when at home, work, or traveling, which will give users more flexibility and freedom. “If you had a 30-pound device that you could put in the overhead bins when traveling, you could go visit your grandkids,” he says.
Kurtz’s team at UCLA partnered with the U.S. Kidney Research Corporation and Arkansas University to develop a dialysate-free desktop device (about the size of a small printer) as the first phase of a progression that will he hopes will lead to something small and implantable. Part of the reason for the artificial kidney’s size, Kurtz says, is the number of functions his team are cramming into it. Not only will it filter urea from blood, but it will also use electricity to help regulate electrolyte levels in a process called electrodeionization. Kurtz emphasizes that these additional functions are what makes his design a true artificial kidney instead of just a small dialysis machine.
One version of an artificial kidney.
UCLA
“It doesn't have just a static function. It has a bank of sensors that measure chemicals in the blood and feeds that information back to the device,” Kurtz says.
Other startups are getting in on the game. Nephria Bio, a spinout from the South Korean-based EOFlow, is working to develop a wearable dialysis device, akin to an insulin pump, that uses miniature cartridges with nanomaterial filters to clean blood (Harhay is a scientific advisor to Nephria). Ian Welsford, Nephria’s co-founder and CTO, says that the device’s design means that it can also be used to treat acute kidney injuries in resource-limited settings. These potentials have garnered interest and investment in artificial kidneys from the U.S. Department of Defense.
For his part, Burton is most interested in an implantable device, as that would give him the most freedom. Even having a regular outpatient procedure to change batteries or filters would be a minor inconvenience to him.
“Being plugged into a machine, that’s not mimicking life,” he says.
Avalanche rescue dogs train to find and dig out people buried in snow slides
By the time he is three, Lume, like Huckleberry, will be a fully trained avy pup and will join seven other avy dogs on Breckenridge ski patrol team. Some of the team members, both human and canine, are also certified to work with Colorado Rapid Avalanche Deployment, a coordinated response team that works with the Summit County Sheriff’s office for avalanche emergencies outside of the ski slopes’ boundaries.
There have been 19 avalanche deaths in the U.S. this season, according to avalanche.org, which tracks slides; eight in Colorado. During the entirety of last season there were 17. Avalanche season runs from November through June, but avalanches can occur year-round.
High tech and high stakes
Complementing avy dogs’ ability to smell people buried in a slide, avalanche detection, rescue and recovery is becoming increasingly high tech. There are transceivers, signal locators, ground scanners and drones, which are considered “games changers” by many in avalanche rescue and recovery
For a person buried in an avalanche, the chance of survival plummets after 20 minutes, so every moment counts.
A drone can provide thermal imaging of objects caught in a slide; what looks like a rock from far away might be a human with a heat signature. Transceivers, also known as beacons, send a signal from an avalanche victim to a companion. Signal locators, like RECCO reflectors which are often sewn directly into gear, can echo back a radar signal sent by a detector; most ski resorts have RECCO detector units.
Research suggests that Ground Penetrating Radar (GPR), an electromagnetic tool used by geophysicists to pull images from inside the ground, could be used to locate an avalanche victim. A new study from the Department of Energy’s Sandia National Laboratories suggests that a computer program developed to pinpoint the source of a chemical or biological terrorist attack could also be used to find someone submerged in an avalanche. The search algorithm allows for small robots (described as cockroach-sized) to “swarm” a search area. Researchers say that this distributed optimization algorithm can help find avalanche victims four times faster than current search mechanisms. For a person buried in an avalanche, the chance of survival plummets after 20 minutes, so every moment counts.
An avy dog in training is picking up scent
Sarah McLear
While rescue gear has been evolving, predicting when a slab will fall remains an emerging science — kind of where weather forecasting science was in the 1980s. Avalanche forecasting still relies on documenting avalanches by going out and looking,” says Ethan Greene, director of the Colorado Avalanche Information Center (CAIC). “So if there's a big snowstorm, and as you might remember, most avalanches happened during snowstorms, we could have 10,000 avalanches that release and we document 50,” says Greene. “Avalanche forecasting is essentially pattern recognition,” he adds--and understanding the layering structure of snow.
However, determining where the hazards lie can be tricky. While a dense layer of snow over a softer, weaker layer may be a recipe for an avalanche, there’s so much variability in snowpack that no one formula can predict the trigger. Further, observing and measuring snow at a single point may not be representative of all nearby slopes. Finally, there’s not enough historical data to help avalanche scientists create better prediction models.
That, however, may be changing.
Last year, an international group of researchers created computer simulations of snow cover using 16 years of meteorological data to forecast avalanche hazards, publishing their research in Cold Regions Science and Technology. They believe their models, which categorize different kinds of avalanches, can support forecasting and determine whether the avalanche is natural (caused by temperature changes, wind, additional snowfall) or artificial (triggered by a human or animal).
With smell receptors ranging from 800 million for an average dog, to 4 billion for scent hounds, canines remain key to finding people caught in slides.
With data from two sites in British Columbia and one in Switzerland, researchers built computer simulations of five different avalanche types. “In terms of real time avalanche forecasting, this has potential to fill in a lot of data gaps, where we don't have field observations of what the snow looks like,” says Simon Horton, a postdoctoral fellow with the Simon Fraser University Centre for Natural Hazards Research and a forecaster with Avalanche Canada, who participated in the study. While complex models that simulate snowpack layers have been around for a few decades, they weren’t easy to apply until recently. “It's been difficult to find out how to apply that to actual decision-making and improving safety,” says Horton. If you can derive avalanche problem types from simulated snowpack properties, he says, you’ll learn “a lot about how you want to manage that risk.”
The five categories include “new snow,” which is unstable and slides down the slope, “wet snow,” when rain or heat makes it liquidly, as well as “wind-drifted snow,” “persistent weak layers” and “old snow.” “That's when there's some type of deeply buried weak layer in the snow that releases without any real change in the weather,” Horton explains. “These ones tend to cause the most accidents.” One step by a person on that structurally weak layer of snow will cause a slide. Horton is hopeful that computer simulations of avalanche types can be used by scientists in different snow climates to help predict hazard levels.
Greene is doubtful. “If you have six slopes that are lined up next to each other, and you're going to try to predict which one avalanches and the exact dimensions and what time, that's going to be really hard to do. And I think it's going to be a long time before we're able to do that,” says Greene.
What both researchers do agree on, though, is that what avalanche prediction really needs is better imagery through satellite detection. “Just being able to count the number of avalanches that are out there will have a huge impact on what we do,” Greene says. “[Satellites] will change what we do, dramatically.” In a 2022 paper, scientists at the University of Aberdeen in England used satellites to study two deadly Himalayan avalanches. The imaging helped them determine that sediment from a 2016 ice avalanche plus subsequent snow avalanches contributed to the 2021 avalanche that caused a flash flood, killing over 200 people. The researchers say that understanding the avalanches characteristics through satellite imagery can inform them how one such event increases the magnitude of another in the same area.
Avy dogs trainers hide in dug-out holes in the snow, teaching the dogs to find buried victims
Sarah McLear
Lifesaving combo: human tech and Mother Nature’s gear
Even as avalanche forecasting evolves, dogs with their built-in rescue mechanisms will remain invaluable. With smell receptors ranging from 800 million for an average dog, to 4 billion for scent hounds, canines remain key to finding people caught in slides. (Humans in comparison, have a meager 12 million.) A new study published in the Journal of Neuroscience revealed that in dogs smell and vision are connected in the brain, which has not been found in other animals. “They can detect the smell of their owner's fingerprints on a glass slide six weeks after they touched it,” says Nicholas Dodman, professor emeritus at Cummings School of Veterinary Medicine at Tufts University. “And they can track from a boat where a box filled with meat was buried in the water, 100 feet below,” says Dodman, who is also co-founder and president of the Center for Canine Behavior Studies.
Another recent study from Queens College in Belfast, United Kingdom, further confirms that dogs can smell when humans are stressed. They can also detect the smell of a person’s breath and the smell of the skin cells of a deceased person.
The emerging avalanche-predicting human-made tech and the incredible nature-made tech of dogs’ olfactory talents is the lifesaving “equipment” that Leffler believes in. Even when human-made technology develops further, it will be most efficient when used together with the millions of dogs’ smell receptors, Leffler believes. “It is a combination of technology and the avalanche dog that will always be effective in finding an avalanche victim.”
