A future app may help you avoid getting the flu by informing you of your local risk on a given day.
Applied mathematician Sara del Valle works at the U.S.'s foremost nuclear weapons lab: Los Alamos. Once colloquially called Atomic City, it's a hidden place 45 minutes into the mountains northwest of Santa Fe. Here, engineers developed the first atomic bomb.
Like AccuWeather, an app for disease prediction could help people alter their behavior to live better lives.
Today, Los Alamos still a small science town, though no longer a secret, nor in the business of building new bombs. Instead, it's tasked with, among other things, keeping the stockpile of nuclear weapons safe and stable: not exploding when they're not supposed to (yes, please) and exploding if someone presses that red button (please, no).
Del Valle, though, doesn't work on any of that. Los Alamos is also interested in other kinds of booms—like the explosion of a contagious disease that could take down a city. Predicting (and, ideally, preventing) such epidemics is del Valle's passion. She hopes to develop an app that's like AccuWeather for germs: It would tell you your chance of getting the flu, or dengue or Zika, in your city on a given day. And like AccuWeather, it could help people alter their behavior to live better lives, whether that means staying home on a snowy morning or washing their hands on a sickness-heavy commute.
Sara del Valle of Los Alamos is working to predict and prevent epidemics using data and machine learning.
Since the beginning of del Valle's career, she's been driven by one thing: using data and predictions to help people behave practically around pathogens. As a kid, she'd always been good at math, but when she found out she could use it to capture the tentacular spread of disease, and not just manipulate abstractions, she was hooked.
When she made her way to Los Alamos, she started looking at what people were doing during outbreaks. Using social media like Twitter, Google search data, and Wikipedia, the team started to sift for trends. Were people talking about hygiene, like hand-washing? Or about being sick? Were they Googling information about mosquitoes? Searching Wikipedia for symptoms? And how did those things correlate with the spread of disease?
It was a new, faster way to think about how pathogens propagate in the real world. Usually, there's a 10- to 14-day lag in the U.S. between when doctors tap numbers into spreadsheets and when that information becomes public. By then, the world has moved on, and so has the disease—to other villages, other victims.
"We found there was a correlation between actual flu incidents in a community and the number of searches online and the number of tweets online," says del Valle. That was when she first let herself dream about a real-time forecast, not a 10-days-later backcast. Del Valle's group—computer scientists, mathematicians, statisticians, economists, public health professionals, epidemiologists, satellite analysis experts—has continued to work on the problem ever since their first Twitter parsing, in 2011.
They've had their share of outbreaks to track. Looking back at the 2009 swine flu pandemic, they saw people buying face masks and paying attention to the cleanliness of their hands. "People were talking about whether or not they needed to cancel their vacation," she says, and also whether pork products—which have nothing to do with swine flu—were safe to buy.
At the latest meeting with all the prediction groups, del Valle's flu models took first and second place.
They watched internet conversations during the measles outbreak in California. "There's a lot of online discussion about anti-vax sentiment, and people trying to convince people to vaccinate children and vice versa," she says.
Today, they work on predicting the spread of Zika, Chikungunya, and dengue fever, as well as the plain old flu. And according to the CDC, that latter effort is going well.
Since 2015, the CDC has run the Epidemic Prediction Initiative, a competition in which teams like de Valle's submit weekly predictions of how raging the flu will be in particular locations, along with other ailments occasionally. Michael Johannson is co-founder and leader of the program, which began with the Dengue Forecasting Project. Its goal, he says, was to predict when dengue cases would blow up, when previously an area just had a low-level baseline of sick people. "You'll get this massive epidemic where all of a sudden, instead of 3,000 to 4,000 cases, you have 20,000 cases," he says. "They kind of come out of nowhere."
But the "kind of" is key: The outbreaks surely come out of somewhere and, if scientists applied research and data the right way, they could forecast the upswing and perhaps dodge a bomb before it hit big-time. Questions about how big, when, and where are also key to the flu.
A big part of these projects is the CDC giving the right researchers access to the right information, and the structure to both forecast useful public-health outcomes and to compare how well the models are doing. The extra information has been great for the Los Alamos effort. "We don't have to call departments and beg for data," says del Valle.
When data isn't available, "proxies"—things like symptom searches, tweets about empty offices, satellite images showing a green, wet, mosquito-friendly landscape—are helpful: You don't have to rely on anyone's health department.
At the latest meeting with all the prediction groups, del Valle's flu models took first and second place. But del Valle wants more than weekly numbers on a government website; she wants that weather-app-inspired fortune-teller, incorporating the many diseases you could get today, standing right where you are. "That's our dream," she says.
This plot shows the the correlations between the online data stream, from Wikipedia, and various infectious diseases in different countries. The results of del Valle's predictive models are shown in brown, while the actual number of cases or illness rates are shown in blue.
(Courtesy del Valle)
The goal isn't to turn you into a germophobic agoraphobe. It's to make you more aware when you do go out. "If you know it's going to rain today, you're more likely to bring an umbrella," del Valle says. "When you go on vacation, you always look at the weather and make sure you bring the appropriate clothing. If you do the same thing for diseases, you think, 'There's Zika spreading in Sao Paulo, so maybe I should bring even more mosquito repellent and bring more long sleeves and pants.'"
They're not there yet (don't hold your breath, but do stop touching your mouth). She estimates it's at least a decade away, but advances in machine learning could accelerate that hypothetical timeline. "We're doing baby steps," says del Valle, starting with the flu in the U.S., dengue in Brazil, and other efforts in Colombia, Ecuador, and Canada. "Going from there to forecasting all diseases around the globe is a long way," she says.
But even AccuWeather started small: One man began predicting weather for a utility company, then helping ski resorts optimize their snowmaking. His influence snowballed, and now private forecasting apps, including AccuWeather's, populate phones across the planet. The company's progression hasn't been without controversy—privacy incursions, inaccuracy of long-term forecasts, fights with the government—but it has continued, for better and for worse.
Disease apps, perhaps spun out of a small, unlikely team at a nuclear-weapons lab, could grow and breed in a similar way. And both the controversies and public-health benefits that may someday spin out of them lie in the future, impossible to predict with certainty.
A movie still from the 1966 film "Fantastic Voyage"
"Chemotherapy is delivered systemically," Bionaut-founder and CEO Michael Shpigelmacher says. "Often only a small percentage arrives at the location where it is actually needed."
But what if it was possible to send a tiny robot through the body to attack a tumor or deliver a drug at exactly the right location?
Several startups and academic institutes worldwide are working to develop such a solution but Bionaut Labs seems the furthest along in advancing its invention. "You can think of the Bionaut as a tiny screw that moves through the veins as if steered by an invisible screwdriver until it arrives at the tumor," Shpigelmacher explains. Via Zoom, he shares the screen of an X-ray machine in his Culver City lab to demonstrate how the half-transparent, yellowish device winds its way along the spine in the body. The nanobot contains a tiny but powerful magnet. The "invisible screwdriver" is an external magnetic field that rotates that magnet inside the device and gets it to move and change directions.
The current model has a diameter of less than a millimeter. Shpigelmacher's engineers could build the miniature vehicle even smaller but the current size has the advantage of being big enough to see with bare eyes. It can also deliver more medicine than a tinier version. In the Zoom demonstration, the micorobot is injected into the spine, not unlike an epidural, and pulled along the spine through an outside magnet until the Bionaut reaches the brainstem. Depending which organ it needs to reach, it could be inserted elsewhere, for instance through a catheter.
"The hope is that we can develop a vehicle to transport medication deep into the body."
Imagine moving a screw through a steak with a magnet — that's essentially how the device works. But of course, the Bionaut is considerably different from an ordinary screw: "At the right location, we give a magnetic signal, and it unloads its medicine package," Shpigelmacher says.
To start, Bionaut Labs wants to use its device to treat Parkinson's disease and brain stem gliomas, a type of cancer that largely affects children and teenagers. About 300 to 400 young people a year are diagnosed with this type of tumor. Radiation and brain surgery risk damaging sensitive brain tissue, and chemotherapy often doesn't work. Most children with these tumors live less than 18 months. A nanobot delivering targeted chemotherapy could be a gamechanger. "These patients really don't have any other hope," Shpigelmacher says.
Of course, the main challenge of the developing such a device is guaranteeing that it's safe. Because tissue is so sensitive, any mistake could risk disastrous results. Over the past four years, Bionaut has tested its technology in dozens of healthy sheep and pigs with no major adverse effects. Sheep make a good stand-in for humans because their brains and spines are similar to ours.
The Bionaut device is about the size of a grain of rice.
Bionaut Labs
"As the Bionaut moves through brain tissue, it creates a transient track that heals within a few weeks," Shpigelmacher says. The company is hoping to be the first to test a nanobot in humans. That could happen as early as 2023, Shpigelmacher says.
Once the technique has been perfected, further applications could include addressing other kinds of brain disorders that are considered incurable now, such as Alzheimer's or Huntington's disease. "Microrobots could serve as a bridgehead, opening the gateway to the brain and facilitating precise access of deep brain structure – either to deliver medication, take cell samples or stimulate specific brain regions," Shpigelmacher says.
Robot-assisted hybrid surgery with artificial intelligence is already used in state-of-the-art surgery centers, and many medical experts believe that nanorobotics will be the instrument of the future. In 2016, three scientists were awarded the Nobel Prize in Chemistry for their development of "the world's smallest machines," nano "elevators" and minuscule motors. Since then, the scientific experiments have progressed to the point where applicable devices are moving closer to actually being implemented.
Bionaut's technology was initially developed by a research team lead by Peer Fischer, head of the independent Micro Nano and Molecular Systems Lab at the Max Planck Institute for Intelligent Systems in Stuttgart, Germany. Fischer is considered a pioneer in the research of nano systems, which he began at Harvard University more than a decade ago. He and his team are advising Bionaut Labs and have licensed their technology to the company.
"The hope is that we can develop a vehicle to transport medication deep into the body," says Max Planck scientist Tian Qiu, who leads the cooperation with Bionaut Labs. He agrees with Shpigelmacher that the Bionaut's size is perfect for transporting medication loads and is researching potential applications for even smaller nanorobots, especially in the eye, where the tissue is extremely sensitive. "Nanorobots can sneak through very fine tissue without causing damage."
In "Fantastic Voyage," Raquel Welch's adventures inside the body of a dissident scientist let her swim through his veins into his brain, but her shrunken miniature submarine is attacked by antibodies; she has to flee through the nerves into the scientist's eye where she escapes into freedom on a tear drop. In reality, the exit in the lab is much more mundane. The Bionaut simply leaves the body through the same port where it entered. But apart from the dramatization, the "Fantastic Voyage" was almost prophetic, or, as Shpigelmacher says, "Science fiction becomes science reality."
