A future app may help you avoid getting the flu by informing you of your local risk on a given day.
(© Dmytro Flisak/Adobe)
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 biotech in Cambridge, Mass., is targeting a rare disease called cystinosis with gene therapy. It's been effective for five patients in a clinical trial that's still underway.
Cherqui Lab
Recently, AVROBIO compiled positive clinical data from this first and only gene therapy trial for the disease. The data show the potential of the therapy to genetically modify the patients’ own hematopoietic stem cells—a certain type of cell that’s capable of developing into all different types of blood cells—to express the functional protein they are deficient in. It stabilizes or reduces the impact of cystinosis on multiple tissues with a single dose.
Medical researchers have found that more than 80 different mutations to a gene called CTNS are responsible for causing cystinosis. The most common mutation results in a deficiency of the protein cystinosin. That protein functions as a transporter that regulates a lot metabolic processes in the cells.
“One of the first things we see in patients clinically is an accumulation of a particular amino acid called cystine, which grows toxic cystine crystals in the cells that cause serious complications,” explains Essra Rihda, chief medical officer for AVROBIO. “That happens in the cells across the tissues and organs of the body, so the disease affects many parts of the body.”
Jordan Janz, 23, meets Stephanie Cherqui, the principal investigator of his gene therapy trial, before the trial started in 2019.
Jordan Janz
According to Rihda, although cystinosis can occur in kids and adults, the most severe form of the disease affects infants and makes up about 95 percent of overall cases. Children typically appear healthy at birth, but around six to 18 months, they start to present for medical attention with failure to thrive.
Additionally, infants with cystinosis often urinate frequently, a sign of polyuria, and they are thirsty all the time, since the disease usually starts in the kidneys. Many develop chronic kidney disease that ultimately progresses to the point where the kidney no longer supports the body’s needs. At that stage, dialysis is required and then a transplant. From there the disease spreads to many other organs, including the eyes, muscles, heart, nervous system, etc.
“The gene for cystinosis is expressed in every single tissue we have, and the accumulation of this toxic buildup alters all of the organs of the patient, so little by little all of the organs start to fail,” says Stephanie Cherqui, principal investigator of Cherqui Lab, which is part of UC San Diego’s Department of Pediatrics.
Since the 1950s, a drug called cysteamine showed some therapeutic effect on cystinosis. It was approved by the FDA in 1994 to prevent damage that may be caused by the buildup of cystine crystals in organs. Prior to FDA approval, Cherqui says, children were dying of the disease before they were ten-years-old or after a kidney transplant. By taking oral cysteamine, they can live from 20 to 50 years longer. But it’s a challenging drug because it has to be taken every 6 or 12 hours, and there are serious gastric side effects such as nausea and diarrhea.
“With all of the complications they develop, the typical patient takes 40 to 60 pills a day around the clock,” Cherqui says. “They literally have a suitcase of medications they have to carry everywhere, and all of those medications don’t stop the progression of the disease, and they still die from it.”
Cherqui has been a proponent of gene therapy to treat children’s disorders since studying cystinosis while earning her doctorate in 2002. Today, her lab focuses on developing stem cell and gene therapy strategies for degenerative, hereditary disorders such as cystinosis that affect multiple systems of the body. “Because cystinosis expresses in every tissue in the body, I decided to use the blood-forming stem cells that we have in our bone marrow,” she explains. “These cells can migrate to anywhere in the body where the person has an injury from the disease.”
AVROBIO’s hematopoietic stem cell gene therapy approach collects stem cells from the patient’s bone marrow. They then genetically modify the stem cells to give the patient a copy of the healthy CTNS gene, which the person either doesn’t have or it’s defective.
The patient first undergoes apheresis, a medical procedure in which their blood is passed through an apparatus that separates out the diseased stem cells, and a process called conditioning is used to help eliminate the damaged cells so they can be replaced by the infusion of the patient’s genetically modified stem cells. Once they become engrafted into the patient’s bone marrow, they reproduce into a lot of daughter cells, and all of those daughter cells contain the CTNS gene. Those cells are able to express the healthy, functional, active protein throughout the body to correct the metabolic problem caused by cystinosis.
“What we’re seeing in the adult patients who have been dosed to date is the consistent and sustained engraftment of our genetically modified cells, 17 to 27 months post-gene therapy, so that’s very encouraging and positive,” says Rihda, the chief medical officer at AVROBIO.
When Janz was 11-years-old, his mother got him enrolled in the trial of a new form of cysteamine that would only need to be taken every 12 hours instead of every six. Two years later, she made sure he was the first person on the list for Cherqui’s current stem cell gene therapy trial.
AVROBIO researchers have also confirmed stabilization or improvement in motor coordination and visual perception in the trial participants, suggesting a potential impact on the neuropathology of the disease. Data from five dosed patients show strong safety and tolerability as well as reduced accumulation of cystine crystals in cells across multiple tissues in the first three patients. None of the five patients need to take oral cysteamine.
Janz’s mother, Barb Kulyk, whom he credits with always making him take his medications and keeping him hydrated, had been following Cherqui’s research since his early childhood. When Janz was 11-years-old, she got him enrolled in the trial of a new form of cysteamine that would only need to be taken every 12 hours instead of every six. When he was 17, the FDA approved that drug. Two years later, his mother made sure he was the first person on the list for Cherqui’s current stem cell gene therapy trial. He received his new stem cells on October 7th, 2019, went home in January 2020, and returned to working full time in February.
Jordan Janz, pictured here with his girlfriend, has a new lease on life, plus a new hair color.
Jordan Janz
He notes that his energy level is significantly better, and his mother has noticed much improvement in him and his daily functioning: He rarely vomits or gets nauseous in the morning, and he has more color in his face as well as his hair. Although he could finish his participation at any time, he recently decided to continue in the clinical trial.
Before the trial, Janz was taking 56 pills daily. He is completely off all of those medications and only takes pills to keep his kidneys working. Because of the damage caused by cystinosis over the course of his life, he’s down to about 20 percent kidney function and will eventually need a transplant.
“Some day, though, thanks to Dr. Cherqui’s team and AVROBIO’s work, when I get a new kidney, cystinosis won’t destroy it,” he concludes.