The first time I remember hearing the words “biology’s century,” it was a sales pitch.
I was standing by the Long Island Sound in Sachem’s Head, Conn., in the shadow of an 11-foot-tall granite Stonehenge replica built by Jonathan Rothberg, a biotech entrepreneur, as he talked up his newest gadget, a tabletop DNA sequencer. It was 2010.
Near his monument to the ancient past, Rothberg was conjuring a vision of the future, one based on harnessing the power of biology and technology to transform the world. The phrase he uttered wasn’t new, having been in circulation since the Human Genome Project in the 1990s, and I’d been covering biotech for a decade. But that was the moment the phrase sunk in. I added it to my Twitter bio, where it has remained.
Over the next decade, I’d see even more amazing things. Genetically altered white blood cells that can cure cancer. A gene therapy that gave sight to blind children. Pills that wrench decades of life from a cancer death sentence or ease the breathing of patients with cystic fibrosis. And, of course, not one but several effective Covid-19 vaccines created only a year into a once-in-a-century pandemic.
Here’s what “biology’s century” means to me: In the same way the 20th century belonged to physics, the 21st is biological. But while physics in the 20th century brought airplanes, personal computers, and posters of Albert Einstein, it also meant the atom bomb and a complete transformation of the social order.
Now, we’re approaching a moment when changes in what we understand about biology are every bit as exhilarating and terrifying.
We now sequence the genes of people, animals, plants and tumors routinely. We’re starting to edit DNA, not only in individual cells but even inside living people, as a treatment. Drug companies have created therapies for previously unconquerable diseases from melanoma to spinal muscular atrophy. Artificial intelligence, machine learning, and other computer tools aim to speed up the process further.
So what’s the biological equivalent of the atom bomb? Sure, there are worries that we’ll edit the wrong genes, or create biological inequality to mirror the economic inequality we already have. But the biggest looming problem is that we will simply become lost and confused as to what works and what doesn’t, scuttling our own progress, wasting money, and missing opportunities to save lives. That’s what happens when new technologies in biology outpace our ability to assess them.
When a new plane is tested, there is little doubt as to whether or not it can fly. But new medicines that enter human studies fail 90% of the time, and often, even when they are on the market and are very effective, large studies can be needed to be sure they are doing more good than harm. But we’re not doing these studies, called clinical trials, right. We’re embracing shortcuts called “real-world evidence” in place of rigorous studies that randomize patients to receive one treatment or another. Our electronic health records, a key to moving forward, are siloed and maddeningly unstructured. And we haven’t figured out how to deal with other biotechnologies that aim to change manufacturing, bring back extinct animals, or change how crops are grown.
I loved the phrase “biology’s century” from the moment I heard Rothberg say it. But I also remember that, walking on paths along that Connecticut cliffside, I almost slipped. Rothberg steadied me, and joked that it would be bad press if the reporter died.
Looking at the current crop of biotechnologies, from AI to gene editing to blood tests that can detect cancer, I feel like I’m once again in the shadow of that imitation Stonehenge. The view is beautiful. But I worry we’re about to topple into the ocean.
To understand how fast biotech is moving, consider Jimi Olaghere, a tech entrepreneur who suffered from sickle cell anemia for his entire life.
Sickle cell is an inherited disease caused by misshapen blood cells that slow or block blood flow, resulting in painful symptoms. It afflicts 100,000 Americans, most of them Black. Olaghere spent his early childhood in Nigeria, where it was shaped by the disease, which made it difficult for him to keep up with other children. His family moved to the U.S. in part for better medical care. Planes had to abort their journeys because he had symptoms in flight. “I had my honeymoon interrupted by a sickle cell crisis,” Olaghere said at a STAT event in March. He made multiple trips to the ICU. He chose a career in which frequent bouts of sickness wouldn’t be as big a barrier to success. “For many moments it felt like sickle cell was a puppet master, dictating what I did with my life,” he said.
But Olaghere found a treatment in a clinical trial that he says has helped him, allowing him to live a more normal life and to savor simple experiences like parenting his kids. Researchers removed cells from his blood and used the new gene editing technology CRISPR to edit their DNA. Then, after using a medicine to clear out his existing bone marrow, a grueling regimen, the new cells were injected in. These new cells produced normal red blood cells, nearly eliminating the need for transfusions. The treatment is being developed by two biotechnology companies, Vertex Pharmaceuticals and CRISPR Therapeutics.
I was one of the first journalists to write about the discovery of CRISPR in 2012. That work won the researchers behind it a Nobel Prize. But at the time the research just looked like something that would be used in the laboratory. That it would be used to edit the genes of patients in less than a decade was simply inconceivable then.
But that’s what happened, and it’s a sign of a larger explosion in biotech advancements. Most people don’t realize it, but this is a golden age of drug discovery and biomedical innovation. From 2012 through 2021, the Food and Drug Administration’s Center for Drug Evaluation and Research approved 430 new medicines, up 73% from the preceding decade and 25% more than the one before that, once seen as a golden era for drug development. Some vaccines and protein therapies are not even included in this tally. Medicines approved in this era have included dozens of new treatments for cancer including immunotherapies; diabetes medicines that also fight obesity; and vaccines against shingles, Ebola, and meningitis. They’ve also included the first gene therapies. The Covid vaccines are, of course, the pièce de résistance.
But like an athlete testing her top speed, pushing medicine’s limits shows exactly where those limits are. Other researchers are hoping to use CRISPR for much more common diseases, including heart attacks. That will require far larger studies that will involve many thousands of patients. And the rate-limiting step for developing CRISPR will soon cease to be making technical advancements to gene editing enzymes and will instead become testing CRISPR treatments to figure out how well they work — or don’t.
The consequence of widespread testing is not just that we learn whether a medicine is effective, but also how safe it is. This tough lesson reshaped the drug industry two decades ago.
Late at night on Sept. 29, 2004, I got a phone call from a PR person at Merck telling me I’d want to be at a New York City hotel early the next morning. Merck was holding a press conference to reveal it was withdrawing the arthritis drug Vioxx, one of the biggest blockbusters of its era. For years, critics had alleged the medicine caused heart attacks. Merck had fought back, but now one of its own clinical trials proved that the allegations were true.
What followed was a period of several years when safety concerns were raised about one new medicine after another. The antidepressant Paxil was linked to suicidal thoughts in adolescents (this link is still controversial). The antibiotic Ketek saw its use plummet after it was linked to acute liver failure. Avandia, the best-selling diabetes pill of its time, saw sales crash after concerns were raised that it, too, might be linked to heart problems. Big sellers like Zelnorm, for irritable bowel syndrome, Bextra, for arthritis, and Meridia for weight loss were withdrawn from the market entirely. It seemed biology was teaching medicine a cruel lesson: trying to use a chemical to treat a disease always came with a cost of side effects.
This period now seems like it happened in an alternate reality. Big drug safety controversies are now rare. But that’s not because scientists have somehow figured out how to develop drugs that don’t come with safety tradeoffs. It’s because, in a way, we’ve stopped looking for them.
Medicine’s infrastructure problem
To understand the scale of the problem, consider exactly how much data researchers need to amass to prove a medicine is truly effective.
The cholesterol drugs known as statins — atorvastatin, rosuvastatin, simvastatin — are among the most prescribed medicines in the country, and even so public health experts say more people should be taking them for their proven ability to prevent heart attacks and strokes. Years after its patent expired atorvastatin — it used to be called Lipitor — is the most used drug in America.
But it took a gigantic amount of research to establish statins’ benefits. The first statin, originally derived from fungal broths, was approved in 1986. The first evidence statins prevent second heart attacks in people who had already had one came from a 4,444-patient study of a Merck drug, simvastatin, in 1994.
Proving a medicine like this works means randomly giving thousands of people either the drug or a placebo and counting heart attacks, strokes, episodes of chest pain, and heart procedures. This is the bottleneck: enrolling people in studies and counting their heart attacks. The core technology is not the drug molecule but randomization, randomly assigning patients to get one thing or another. This is the only way researchers can be sure that people who get the drug live longer, and the outcome is not due to chance.
Over 20 years, researchers conducted at least 27 different statin clinical trials involving 174,000 volunteers. The studies showed the drugs reduce the risk of death.
The benefits of running these trials were huge. One analysis estimates that the development of these drugs meant there were 40,000 fewer deaths, 60,000 fewer hospitalizations for heart attacks, and 22,000 fewer strokes in 2008 compared to 1987, saving society $1.3 trillion while generating $300 billion in revenue for drugmakers.
But over time the cost per patient in such studies has gone up, as has the number of patients in each study. When Regeneron and Sanofi tried to introduce a new cholesterol-lowering shot in 2015, they said a 30,000-patient group of studies containing a single large trial cost upward of $1 billion. The drug was a big disappointment, failing to justify the cost for the companies.
“Certainly the cost of clinical trials has become so outrageous we have to do something to change it,” said George Yancopoulos, Regeneron’s co-founder and chief scientific officer. He remembers that when he started it cost $10,000 per patient to conduct a clinical trial. Now it can cost $500,000, he said. “Just think how expensive that can be. It really limits what we can do.”
Instead of dealing with the difficulty of collecting data on new medicines, both society and government sidestepped it by focusing on treatments for much rarer illnesses: relatively rare cancers, rheumatoid arthritis, and multiple sclerosis to name a few, not to mention very rare illnesses such as cystic fibrosis or paroxysmal nocturnal hemoglobinuria.
There’s nothing wrong with this — people suffering from those diseases need treatment, too, and their benefits can be more immediately apparent than for diseases such as heart disease or diabetes. But this focus allowed companies to conduct smaller trials and then charge much higher prices. That’s one reason that, between 2007 and 2021, the average price of a new medicine rose from $2,115 to $180,007, and the proportion of drugs that cost more than $150,000 rose from 9% to 47%.
In some cancers, randomized trials are not even required by regulators, because shrinking tumors is considered enough to show there is a benefit for those with no other hope. This frequently occurs with so-called “precision” medicines based on cancer genetics. But too often this means studies testing drugs in less sick patients happen slowly or not at all.
“It’s getting harder and harder to do a randomized trial for some of these precision drugs,” said Otis Brawley, a professor of oncology and epidemiology at Johns Hopkins University. “There’s a leap of faith that the drug actually works.”
“I think the randomized trial is getting close to the end of its run,” Brawley worried. Yet, he said, “I think it’s the only way to prove real science.”
Richard Pazdur, who heads the FDA office that evaluates new drugs, has even recently pushed back against these single-armed studies. But the big problem, again, is not what regulators are requiring. It is that conducting these trials is so, so difficult.
“My personal thought is that the trial infrastructure sucks,” said Anirban Maitra, scientific director of the Sheikh Ahmed Pancreatic Cancer Research Center at MD Anderson Cancer Center. “We have to do better trials.”
New potential medicines are “everywhere,” Maitra said. “There’s so many assets. There’s great science happening. You don’t need investment in that. And yet 4% of patients are going nationally in trials. And when we look at disparities in these trials, they are awful. To me, if I had the resources, I would make doing trials easier. That’s where I would invest. And if that means having some sort of a national infrastructure? I don’t even know.”
The problem is that in every area, from rare disease to common ailments such as depression, conducting these trials is increasingly difficult and expensive.
Funding every possible clinical trial isn’t a useful answer. With immunotherapy drugs, among the most effective medicines in cancer, drug giants have rushed just about every possible combination into development. Merck alone has funded 211 different clinical trials of its drug, Keytruda, which is already the third-best-selling drug in the world with annual sales of $17.2 billion.
But James Allison, who won a Nobel Prize for his work on developing immunotherapy medicines, thinks this approach is entirely wrong. What is needed is a system for conducting the right smaller studies, where patient samples are collected to understand how the immune system reacts to each new drug combination. Existing studies, he argues, too often simply combine whatever two medicines a pharmaceutical company happens to own.
“All these other trials to me are just offensive because they’re going to fail,” Allison said. He’s set up a new James P. Allison Institute to run those kinds of studies outside the current system.
Learning from Covid
Perhaps the best harbinger of what medicine could look like in the future comes from its biggest crisis: the pandemic.
It’s hard to remember now but when the Pfizer/BioNTech and Moderna vaccines entered large-scale clinical trials, nobody really knew if they would work. On a November Sunday, as researchers waited for the first results to read out, Kathrin Jansen, the head vaccine scientist at Pfizer, called BioNTech CEO Ugur Sahin with some words of comfort.
“We have done our best. We don’t know what is going to happen, but I just wanted to tell you, regardless of what is going to happen, it was great to work with you,” Jansen said.
What made the vaccine trials different from just about any previous studies was that the world’s desperation meant that people lined up to be in them. That allowed all the vaccine manufacturers to rapidly conduct 30,000-volunteer studies. It also helped that Covid infections occurred quickly — unlike with heart attacks or even cancer, participants in studies rapidly developed symptomatic infections, which meant that researchers could quickly see that the vaccines were preventing illness. That’s why, in just a matter of months, not only Pfizer and Moderna but also Johnson & Johnson, AstraZeneca, and Novavax were all able to conduct studies that were just as big and robust as those drugmakers arduously conducted for cholesterol-lowering statin drugs two decades before.
But while the development of the vaccines showed how a crisis can upend the current system and improve it, the development of new medicines intended to treat those who were already sick highlighted every problem within that system. At the start of the Covid pandemic, researchers offered all sorts of theories about medicines — hydroxychloroquine, ivermectin, and tocilizumab among them — that might help to treat Covid.
Yet instead of testing these medicines in studies that could show whether or not they were effective, researchers instead started thousands of small studies that an FDA analysis would later conclude were incapable of determining whether or not the drugs helped patients get better. A STAT analysis showed 25,000 patients were entered into studies of hydroxychloroquine alone.
The pandemic might have been far worse if not for two U.K. academics: Martin Landray and Peter Horby. Soon after the pandemic hit, Landray, a cardiologist who had been involved in many of the big cholesterol drug trials, was already telling officials at the Wellcome Trust, a giant charity, that they needed to run a large clinical trial capable of figuring out what existing medicines could attack the disease. Wellcome put him in touch with Horby, an infectious disease epidemiologist at Oxford.
What Landray and Horby realized was that they could leverage the U.K.’s National Health Service to conduct their study. Most clinical trials try to track every single possible data point about patients, thus inflating costs. But Landry and Horby’s trial could carefully strip down the data needed to the essentials, focusing on information that could easily be collected from medical records. And they managed to get national buy-in from the NHS, so that regular doctors, not just those who had made a business of working with drug companies, would participate.
The result was a single study, RECOVERY, that determined more than any other what medicines could help Covid patients. In June 2020, the study showed that hydroxychloroquine, which had been widely used on hospitalized patients during the deadly Covid outbreak in New York City, was ineffective. Two weeks later, it showed a different cheap medicine, dexamethasone, reduced deaths in patients on ventilators by 35%. The study would also show that monoclonal antibodies and the arthritis drugs baricitinib and tocilizumab reduced the death rate in hospitalized Covid patients, while convalescent plasma, aspirin, and the gout drug colchicine didn’t. Landray and Horby were both knighted for their work in 2021.
It was an impressive effort when other, similar trials couldn’t get off the ground. But that was not the only way that the United Kingdom’s system for collecting health data was able to help doctors understand how to treat Covid patients.
The other was in the use of what researchers call “real-world evidence,” in which data collected from health records and other sources outside of clinical trials are used to track efficacy and side effects. The U.K.’s data were essential to confirming that the vaccines worked as expected once they were in broad use. So were data from Israel, which kept rigorous and organized data from its deployment of the vaccines.
This isn’t just true of clinical data and real-world data. The U.K. has also done a better job of organizing medical data, collecting biological samples and sequencing people’s DNA.
“The U.K. data ecosystem is light years ahead of the United States in terms of the extent that data is collected, the rigor, the quality, the access,” said Daphne Koller, the CEO and founder of Insitro, a biotech focused on artificial intelligence. “Why is it that we as society do such a poor job of systematically collecting data from people in a way that informs our ability to understand human disease and intervention in that disease?” she asks.
At some point, collecting data to determine whether or not treatments work, or to understand why disease occurs, should not simply be the results of studies. It should be a property of a health care system. An ideal system would collect data — and perhaps even conduct randomized controlled trials of different treatments — almost automatically.
So why don’t we have such a system? Part of the answer is that it’s harder than it looks.
But the other is that the U.S. health care system tends to believe that inventing brand new gadgets is the answer to everything. The result is that we try to solve problems by building faster and more expensive Ferraris when what we really need are better roads. As a result, our sports cars end up stuck in the mud. Less metaphorically: We develop medicines that are too expensive for people to take, or ignore potential treatments that could help large groups of people.
“We have constructed a system where cloistering information is the path to profits, where doing the minimal study is the path to profits, where conducting additional studies is just risk,” said Peter Bach, chief medical officer of Delfi Diagnostics. “Even the providers, their primary purpose is not to collect more knowledge but to implement delivery with better margins. In other words, markets work.”
Is there a high-tech solution?
The idea that we should be able to conduct more clinical trials more quickly is far from new. In fact, it is decades old.
One of its biggest proponents was the current FDA commissioner, Robert Califf — starting 40 years ago. Along with Eric Topol, another big name in medicine, he conducted what was called a large simple trial of a clot-busting drug in stroke. The idea was that, as with Landray and Horby’s Covid study decades later, researchers could collect a minimum amount of data and thereby enroll lots of patients.
Later studies were plenty big, but lost the part about collecting data more cheaply. When a blockbuster drug was involved, pharmaceutical companies were quite willing to pay to collect a lot of data. But that led costs to rise, and means big studies are now done mainly when a company has a potentially lucrative product.
Decades later, Califf is still pushing for bigger, simpler trials. He made the need for better data systems and higher standards the point of many of his first public addresses when he took the helm of the FDA for a second time earlier this year. But it’s not clear that the FDA has any power to make this happen. And an FDA commissioner’s time is dominated by other things: questions about drug approvals, baby formula recalls, and negotiations with Congress and industry over the agency’s budget.
Before taking the FDA job, Califf had a different idea of how to fix this data problem: He was working for Alphabet, the company formerly known as Google. At the company’s life sciences research arm, Verily, which was recently backed with $1 billion in funding from its parent company, executives are still trying to imagine the clinical trials of the future.
At the helm of the effort is Amy Abernethy, a former FDA official who is president of Verily’s clinical research platforms. Abernethy told me that she envisions using technologies including Verily’s clinical data platform and a watch used to monitor patients to create studies that follow patients and collect data seamlessly. Once it is easy to use technology to collect data, it would be possible to create randomized trials that are less expensive, larger, and richer in data than those currently conducted. It would, in a way, fulfill Califf’s 40-year-old vision.
The tech industry has widely adopted A/B testing, its version of randomization, as a way to figure out how to get people to click on advertisements on web pages or to keep eyeballs glued to social media sites. It’s not likely, Abernethy said, that medicine is going to be able to dispense with it. But she does believe technology could make placebo groups smaller and studies faster.
“I don’t think the systems of the future can get rid of randomizations,” Abernethy said. “I think we need to be very thoughtful about when we randomize and be very systematic about that.”
The easy way out is dangerous
It’s nice that Verily is thinking in terms of creating randomized controlled trials, not simply large databases, but until now health technology companies have seemed set on doing the opposite. Abernethy previously worked at Flatiron Health, a tech startup that creates databases from a medical record system by hiring people to read doctors’ notes and structure them into data.
Flatiron was sold to Roche in 2018. A spate of other real-world evidence companies emerged. The data they provide are invaluable. They can allow researchers to simulate clinical trials before they run them, preventing large, expensive failures. And they can give doctors insights into how treatment in the real world differs from what happens in studies. But the push from drug companies has been to use real-world evidence as a replacement for good clinical trials.
Too often, Congress seems to support this. There’s rightful outrage that research still doesn’t move fast enough for some rare diseases, such as ALS. A bill in Congress, the Promising Pathway Act, would allow for a temporary two- to six-year provisional approval — something many experts have advocated for since Vioxx. But the bill seems to imagine the evidence of efficacy would come from real-world evidence, not randomized trials.
Drugs that are “not ultimately demonstrated to be sufficiently safe and effective are of no use to patients,” a group of bioethicists wrote in a letter to the sponsors of the bill.
“Through legislation and hearings, Congress continues to push FDA to approve drugs more quickly based on weaker evidence and FDA seems eager to comply,” said Holly Fernandez Lynch, a bioethicist at the University of Pennsylvania and one of the authors of that letter. So far, she said, studies have not shown that real-world evidence is up to the job.
But no matter how much Congress or the president wants to back new research, there’s never any real emphasis on making clinical trials better or easier to conduct. This is not a major thrust of the new ARPA-H division, which would seek to speed biotech research. That focuses on early ideas that are not being funded despite the billions of dollars of venture capital money floating through the system. Nor does Biden’s “cancer moonshot” count building clinical trials as a major goal. Our goal, as a society, seems to be to manufacture more and more sports cars and to drive them faster and faster into the mud.
The problem of being unable to tell what works and what doesn’t, and what is safe and what isn’t, is likely to get worse before it gets better. Companies are now advancing new drugs for heart disease and, in a big advance, for obesity. The focus of the industry is no longer just on rarer diseases.
Another major challenge will be the advent of so-called multi-cancer detection tests. These blood tests, like the one developed by Grail, aim to detect cancer early by sequencing fragments of DNA in the blood, but some critics worry about whether early detection will result in better outcomes for patients.
“The idea that you’re looking for cancer and then you find it in itself I don’t see as a meaningful endpoint,” said Rita Redberg, an expert in screening at the University of California, San Francisco. “You don’t know if these were cancers that were ever going to cause a problem for the person, or if they would have just gone away as many early cancers do.”
Grail, to its credit, is doing a large randomized controlled trial. No surprise: It is being conducted in the United Kingdom, using the National Health Service.
It’s understandable to want to get treatments to patients faster. The way to do that is not to skip studying medicines, but to get better at conducting studies. As it is you can feel the system lurch as it goes from rare diseases to more common ones — and from places where a treatment will save a relatively small number of lives to one where it will save many.
Take the case of CAR-T, one of the most amazing biotech advances of the last decade. In this procedure, a patient’s own T-cells, a type of white blood cell, are removed and genetically re-engineered using a virus so that they attack B-cells, another type of white blood cell that becomes cancerous in forms of leukemia and lymphoma.
CAR-T treatments, now sold by Novartis, Gilead, and Bristol Myers Squibb, were first approved in 2017 for children and adults with no other options. But proving that this new treatment was better than a bone marrow transplant for patients receiving second-line treatment took another five years, and the Novartis study failed while the Gilead and Bristol ones worked. The goal should be to speed up that research, not just get medicines to market sooner and then have them stall.
Douglas Olson was one of the first cancer patients cured by CAR-T 14 years ago. He told STAT that the moment he was told the modified white blood cells were multiplying in his body, everything changed. Over time, he went from being certain he would die to going on distance runs with his sons.
But he’s struck that CAR-T is still not approved for adults with chronic lymphocytic leukemia, the disease he had. It turned out the treatment was less effective in CLL than some other blood cancers, and as new drugs became available conducting CLL studies became a lower priority.
“It was us old guys with CLL that were part of the safety trial that said, ‘Hey, this thing works and we’re going to save lives with it,’” Olson said. “Yet if I had CLL today I couldn’t be treated with CART-19. I don’t get that. It’s the same procedure. It’s not a new drug.”
Industry, government, and academia need to do a better job of making sure that patients aren’t left behind because the right data do not exist.
That means large health care systems and even insurers need to get into the business of conducting clinical trials, instead of just leaving them to pharmaceutical companies. That goes doubly for the National Institutes of Health, which already conducts many important studies but needs to do more. Politicians and regulators outside the health care industry need to start to think about what success and failure look like in medicine.
This is biology’s century. Medical miracles are going to keep emerging. But biology isn’t fair, or predictable, or easy to understand. To take advantage of what is about to happen — indeed, to make sure that new technologies do more good than harm — we need better evidence. It’s not just that we need to do what we are doing better. We, as a society, will need to change our understanding of what is true and what is not. The world’s going to be transformed — we can’t let our thinking about it fall behind.
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