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 recent study by researchers at the University of Pennsylvania examined how CAR-T therapy helped Doug Olson beat a cancer death sentence for over a decade - and how it could work for more people.
Soon afterward, however, his doctor revealed a possible escape route. He and some colleagues at the University of Pennsylvania’s Abramson Cancer Center were starting a clinical trial, he said, and Olson—still mostly symptom-free—might be a good candidate. The experimental treatment, known as CAR-T therapy, would use genetic engineering to turn his T lymphocytes (immune cells that guard against viruses and other pathogens) into a weapon against cancer.
In September 2010, technicians took some of Olson’s T cells to a laboratory, where they were programmed with new molecular marching orders and coaxed to multiply into an army of millions. When they were ready, a nurse inserted a catheter into his neck. At the turn of a valve, his soldiers returned home, ready to do battle.
“I felt like I’d won the lottery,” Olson says. But he was only the second person in the world to receive this “living drug,” as the University of Pennsylvania investigators called it. No one knew how long his remission would last.
Three weeks later, Olson was slammed with a 102-degree fever, nausea, and chills. The treatment had triggered two dangerous complications: cytokine release syndrome, in which immune chemicals inflame the patient’s tissues, and tumor lysis syndrome, in which toxins from dying cancer cells overwhelm the kidneys. But the crisis passed quickly, and the CAR-T cells fought on. A month after the infusion, the doctor delivered astounding news: “We can’t find any cancer in your body.”
“I felt like I’d won the lottery,” Olson says. But he was only the second person in the world to receive this “living drug,” as the University of Pennsylvania investigators called it. No one knew how long his remission would last.
An Unexpected Cure
In February 2022, the same cancer researchers reported a remarkable milestone: the trial’s first two patients had survived for more than a decade. Although Olson’s predecessor—a retired corrections officer named Bill Ludwig—died of COVID-19 complications in early 2021, both men had remained cancer-free. And the modified immune cells continued to patrol their territory, ready to kill suspected tumor cells the moment they arose.
“We can now conclude that CAR-T cells can actually cure patients with leukemia,” University of Pennsylvania immunologist Carl June, who spearheaded the development of the technique, told reporters. “We thought the cells would be gone in a month or two. The fact that they’ve survived 10 years is a major surprise.”
Even before the announcement, it was clear that CAR-T therapy could win a lasting reprieve for many patients with cancers that were once a death sentence. Since the Food and Drug Administration approved June’s version (marketed as Kymriah) in 2017, the agency has greenlighted five more such treatments for various types of leukemia, lymphoma, and myeloma. “Every single day, I take care of patients who would previously have been told they had no options,” says Rayne Rouce, a pediatric hematologist/oncologist at Texas Children’s Cancer Center. “Now we not only have a treatment option for those patients, but one that could potentially be the last therapy for their cancer that they’ll ever have to receive.”
Immunologist Carl June, middle, spearheaded development of the CAR-T therapy that gave patients Bill Ludwig, left, and Doug Olson, right, a lengthy reprieve on their terminal cancer diagnoses.
Penn Medicine
Yet the CAR-T approach doesn’t help everyone. So far, it has only shown success for blood cancers—and for those, the overall remission rate is 30 to 40 percent. “When it works, it works extraordinarily well,” says Olson’s former doctor, David Porter, director of Penn’s blood and bone marrow transplant program. “It’s important to know why it works, but it’s equally important to know why it doesn’t—and how we can fix that.”
The team’s study, published in the journal Nature, offers a wealth of data on what worked for these two patients. It may also hold clues for how to make the therapy effective for more people.
Building a Better T Cell
Carl June didn’t set out to cure cancer, but his serendipitous career path—and a personal tragedy—helped him achieve insights that had eluded other researchers. In 1971, hoping to avoid combat in Vietnam, he applied to the U.S. Naval Academy in Annapolis, Maryland. June showed a knack for biology, so the Navy sent him on to Baylor College of Medicine. He fell in love with immunology during a fellowship researching malaria vaccines in Switzerland. Later, the Navy deployed him to the Fred Hutchinson Cancer Research Center in Seattle to study bone marrow transplantation.
There, June became part of the first research team to learn how to culture T cells efficiently in a lab. After moving on to the National Naval Medical Center in the ’80s, he used that knowledge to combat the newly emerging AIDS epidemic. HIV, the virus that causes the disease, invades T cells and eventually destroys them. June and his post-doc Bruce Levine developed a method to restore patients’ depleted cell populations, using tiny magnetic beads to deliver growth-stimulating proteins. Infused into the body, the new T cells effectively boosted immune function.
In 1999, after leaving the Navy, June joined the University of Pennsylvania. His wife, who’d been diagnosed with ovarian cancer, died two years later, leaving three young children. “I had not known what it was like to be on the other side of the bed,” he recalls. Watching her suffer through grueling but futile chemotherapy, followed by an unsuccessful bone-marrow transplant, he resolved to focus on finding better cancer treatments. He started with leukemia—a family of diseases in which mutant white blood cells proliferate in the marrow.
Cancer is highly skilled at slipping through the immune system’s defenses. T cells, for example, detect pathogens by latching onto them with receptors designed to recognize foreign proteins. Leukemia cells evade detection, in part, by masquerading as normal white blood cells—that is, as part of the immune system itself.
June planned to use a viral vector no one had tried before: HIV.
To June, chimeric antigen receptor (CAR) T cells looked like a promising tool for unmasking and destroying the impostors. Developed in the early ’90s, these cells could be programmed to identify a target protein, and to kill any pathogen that displayed it. To do the programming, you spliced together snippets of DNA and inserted them into a disabled virus. Next, you removed some of the patient’s T cells and infected them with the virus, which genetically hijacked its new hosts—instructing them to find and slay the patient’s particular type of cancer cells. When the T cells multiplied, their descendants carried the new genetic code. You then infused those modified cells into the patient, where they went to war against their designated enemy.
Or that’s what happened in theory. Many scientists had tried to develop therapies using CAR-T cells, but none had succeeded. Although the technique worked in lab animals, the cells either died out or lost their potency in humans.
But June had the advantage of his years nurturing T cells for AIDS patients, as well as the technology he’d developed with Levine (who’d followed him to Penn with other team members). He also planned to use a viral vector no one had tried before: HIV, which had evolved to thrive in human T cells and could be altered to avoid causing disease. By the summer of 2010, he was ready to test CAR-T therapy against chronic lymphocytic leukemia (CLL), the most common form of the disease in adults.
Three patients signed up for the trial, including Doug Olson and Bill Ludwig. A portion of each man’s T cells were reprogrammed to detect a protein found only on B lymphocytes, the type of white blood cells affected by CLL. Their genetic instructions ordered them to destroy any cell carrying the protein, known as CD19, and to multiply whenever they encountered one. This meant the patients would forfeit all their B cells, not just cancerous ones—but regular injections of gamma globulins (a cocktail of antibodies) would make up for the loss.
After being infused with the CAR-T cells, all three men suffered high fevers and potentially life-threatening inflammation, but all pulled through without lasting damage. The third patient experienced a partial remission and survived for eight months. Olson and Ludwig were cured.
Learning What Works
Since those first infusions, researchers have developed reliable ways to prevent or treat the side effects of CAR-T therapy, greatly reducing its risks. They’ve also been experimenting with combination therapies—pairing CAR-T with chemo, cancer vaccines, and immunotherapy drugs called checkpoint inhibitors—to improve its success rate. But CAR-T cells are still ineffective for at least 60 percent of blood cancer patients. And they remain in the experimental stage for solid tumors (including pancreatic cancer, mesothelioma, and glioblastoma), whose greater complexity make them harder to attack.
The new Nature study offers clues that could fuel further advances. The Penn team “profiled these cells at a level where we can almost say, ‘These are the characteristics that a T cell would need to survive 10 years,’” says Rouce, the physician at Texas Children’s Cancer Center.
One surprising finding involves how CAR-T cells change in the body over time. At first, those that Olson and Ludwig received showed the hallmarks of “killer” T-cells (also known as CD8 cells)—highly active lymphocytes bent on exterminating every tumor cell in sight. After several months, however, the population shifted toward “helper” T-cells (or CD4s), which aid in forming long-term immune memory but are normally incapable of direct aggression. Over the years, the numbers swung back and forth, until only helper cells remained. Those cells showed markers suggesting they were too exhausted to function—but in the lab, they were able not only to recognize but to destroy cancer cells.
June and his team suspect that those tired-looking helper cells had enough oomph to kill off any B cells Olson and Ludwig made, keeping the pair’s cancers permanently at bay. If so, that could prompt new approaches to selecting cells for CAR-T therapy. Maybe starting with a mix of cell types—not only CD8s, but CD4s and other varieties—would work better than using CD8s alone. Or perhaps inducing changes in cell populations at different times would help.
Another potential avenue for improvement is starting with healthier cells. Evidence from this and other trials hints that patients whose T cells are more robust to begin with respond better when their cells are used in CAR-T therapy. The Penn team recently completed a clinical trial in which CLL patients were treated with ibrutinib—a drug that enhances T-cell function—before their CAR-T cells were manufactured. The response rate, says David Porter, was “very high,” with most patients remaining cancer-free a year after being infused with the souped-up cells.
Such approaches, he adds, are essential to achieving the next phase in CAR-T therapy: “Getting it to work not just in more people, but in everybody.”
Doug Olson enjoys nature - and having a future.
Penn Medicine
To grasp what that could mean, it helps to talk with Doug Olson, who’s now 75. In the years since his infusion, he has watched his four children forge careers, and his grandkids reach their teens. He has built a business and enjoyed the rewards of semi-retirement. He’s done volunteer and advocacy work for cancer patients, run half-marathons, sailed the Caribbean, and ridden his bike along the sun-dappled roads of Silicon Valley, his current home.
And in his spare moments, he has just sat there feeling grateful. “You don’t really appreciate the effect of having a lethal disease until it’s not there anymore,” he says. “The world looks different when you have a future.”
In this new video, we capture examples from history when people rejected scientific breakthroughs at first, only for the march of progress to continue.
