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.
As gene therapies and small molecule drugs are being studied in clinical trials, companies increasingly see the value in hiring patients to help explain the potential benefits.
Biomedical corporations and government research agencies are now incorporating patient advocacy more than ever, says Alice Lara, president and CEO of the Sudden Arrhythmia Death Syndromes Foundation in Salt Lake City, Utah. These organizations have seen the effectiveness of including patient voices to communicate and exemplify the benefits that key academic research institutions have shown in their medical studies.
“From our side of the aisle,” Lara says, “what we know as patient advocacy organizations is that educated patients do a lot better. They have a better course in their therapy and their condition, and understanding the genetics is important because all of our conditions are genetic.”
Founded in 2016, Tenaya is advancing gene therapies and small molecule drugs in clinical trials for both prevalent and rare forms of heart disease, says Ali, the CEO.
The firm's first small molecule, now in a Phase 1 clinical trial, is intended to treat heart failure with preserved ejection fraction, where the amount of blood pumped by the heart is reduced due to the heart chambers becoming weak or stiff. The condition accounts for half or more of all heart failure in the U.S., according to Ali, and is growing quickly because it's closely associated with diabetes. It’s also linked with metabolic syndrome, or a cluster of conditions including high blood pressure, high blood sugar, excess body fat around the waist, and abnormal cholesterol levels.
“We have a novel molecule that is first in class and, to our knowledge, best in class to tackle that, so we’re very excited about the clinical trial,” Ali says.
The first phase of the trial is being performed with healthy participants, rather than people with the disease, to establish safety and tolerability. The researchers can also look for the drug in blood samples, which could tell them whether it's reaching its target. Ali estimates that, if the company can establish safety and that it engages the right parts of the body, it will likely begin dosing patients with the disease in 2024.
Tenaya’s therapy delivers a healthy copy of the gene so that it makes a copy of the protein missing from the patients' hearts because of their mutation. The study will start with adult patients, then pivot potentially to children and even newborns, Ali says, “where there is an even greater unmet need because the disease progresses so fast that they have no options.”
Although this work still has a long way to go, Ali is excited about the potential because the gene therapy achieved positive results in the preclinical mouse trial. This animal trial demonstrated that the treatment reduced enlarged hearts, reversed electrophysiological abnormalities, and improved the functioning of the heart by increasing the ejection fraction after the single-dose of gene therapy. That measurement remained stable to the end of the animals’ lives, roughly 18 months, Ali says.
He’s also energized by the fact that heart disease has “taken a page out of the oncology playbook” by leveraging genetic research to develop more precise and targeted drugs and gene therapies.
“Now we are talking about a potential cure of a disease for which there was no cure and using a very novel concept,” says Melind Desai of the Cleveland Clinic.
Tenaya’s second program focuses on developing a gene therapy to mitigate the leading cause of hypertrophic cardiomyopathy through a specific gene called MYPBC3. The disease affects approximately 600,000 patients in the U.S. This particular genetic form, Ali explains, affects about 115,000 in the U.S. alone, so it is considered a rare disease.
“There are infants who are dying within the first weeks to months of life as a result of this mutation,” he says. “There are also adults who start having symptoms in their 20s, 30s and 40s with early morbidity and mortality.” Tenaya plans to apply before the end of this year to get the FDA’s approval to administer an investigational drug for this disease humans. If approved, the company will begin to dose patients in 2023.
“We now understand the genetics of the heart much better,” he says. “We now understand the leading genetic causes of hypertrophic myopathy, dilated cardiomyopathy and others, so that gives us the ability to take these large populations and stratify them rationally into subpopulations.”
Melind Desai, MD, who directs Cleveland Clinic’s Hypertrophic Cardiomyopathy Center, says that the goal of Tenaya’s second clinical study is to help improve the basic cardiac structure in patients with hypertrophic cardiomyopathy related to the MYPBC3 mutation.
“Now we are talking about a potential cure of a disease for which there was no cure and using a very novel concept,” he says. “So this is an exciting new frontier of therapeutic investigation for MYPBC3 gene-positive patients with a chance for a cure.
Neither of Tenaya’s two therapies address the gene mutation that has affected Borsari and her family. But Ali sees opportunity down the road to develop a gene therapy for her particular gene mutation, since it is the second leading cause of cardiomyopathy. Treating the MYH7 gene is especially challenging because it requires gene editing or silencing, instead of just replacing the gene.
Wendy Borsari was diagnosed at age 24 with a commonly inherited heart disease. She joined Tenaya as a patient advocate in 2021.
Wendy Borsari
“If you add a healthy gene it will produce healthy copies,” Ali explains, “but it won’t stop the bad effects of the mutant protein the gene produces. You can only do that by silencing the gene or editing it out, which is a different, more complicated approach.”
Euan Ashley, professor of medicine and genetics at Stanford University and founding director of its Center for Inherited Cardiovascular Disease, is confident that we will see genetic therapies for heart disease within the next decade.
“We are at this really exciting moment in time where we have diseases that have been under-recognized and undervalued now being attacked by multiple companies with really modern tools,” says Ashley, author of The Genome Odyssey. “Gene therapies are unusual in the sense that they can reverse the cause of the disease, so we have the enticing possibility of actually reversing or maybe even curing these diseases.”
Although no one is doing extensive research into a gene therapy for her particular mutation yet, Borsari remains hopeful, knowing that companies such as Tenaya are moving in that direction.
“I know that’s now on the horizon,” she says. “It’s not just some pipe dream, but will happen hopefully in my lifetime or my kids’ lifetime to help them.”
