This story is republished from STAT, the health and medicine news site that’s a partner to the Globe. Sign up for STAT’s free Morning Rounds newsletter here.
Prediction markets have permeated the worlds of sports, politics, and reality television shows. Now, the biopharma industry could be next.
On Thursday, Kalshi, one of the world’s largest prediction market exchanges, said it will start taking bets on clinical trials and regulatory approvals.
It’s starting with a small number of markets chosen in collaboration with its partner, AppliedXL, a tech company that monitors and predicts the outcomes of clinical trials.
Since it’s the first time Kalshi is wading into the space, the company said it will take a conservative approach, allowing people to bet only on the outcomes of Phase 3 trials run by established biopharma companies and with full approval decisions by the Food and Drug Administration.
These markets would have more clear-cut outcomes than early-stage trials, which tend to have exploratory endpoints, and conditional FDA approvals, Kalshi said, but it hopes to expand into those other scenarios in the future if its initial markets work smoothly.
From Kalshi’s perspective, prediction markets can benefit various parties in the biopharma ecosystem. They give investors a more direct way to bet specifically on drug catalysts than is often possible in the stock market, particularly with big companies that are working on multiple candidates. The markets can also gather valuable information to inform drug development, Kalshi argues.
Drugmakers’ decisions about which medicines to advance and invest in are often clouded by internal company politics, but the markets provide “an incentive-aligned external estimate that could sharpen the capital-allocation decisions on which the pace and cost of drug development turn,” Kalshi and AppliedXL said in a white paper accompanying the launch. (STAT’s owner, John Henry, previously invested in AppliedXL, and STAT previously had a partnership with the company focused on tracking and analyzing clinical trials data.)
However, some doctors and researchers register discomfort with the role of prediction markets in their field. Even with precautions put in place, they express concern about the risks of insider trading and manipulation of clinical trials. They also fear the markets could influence the behavior of trial participants and researchers, affecting the integrity of studies that sometimes come with life-or-death consequences for patients.
“Any kind of adulteration that happens in [the clinical trial process] is ultimately threatening the well-being of people who are using that drug and the evidence about it,” said Jonathan Kimmelman, a bioethicist at McGill University.
Initial guardrails
Kalshi and AppliedXL said they’re taking a careful approach and have consulted with several experts, including Kimmelman, as they developed the criteria for their initial markets.
In the case of markets for clinical trials, Kalshi said it will implement an employment verification system and will monitor trading activity to bar insider trading by people employed by the drugmaker running the trials, as well as anyone who has visibility across the trials and to unblinded data, such as lead investigators, lead biostatisticians, and safety-monitoring committee members. Participants in the trials will also be barred from trading.
The exchange is starting with late-stage trials run by larger companies, generally with a market capitalization of over $500 million, said Francesco Marconi, CEO of AppliedXL. Not only will those prediction markets have cleaner outcomes, but they would likely also see greater participation from traders, making them less vulnerable to being swayed by any one potential insider trade trying to influence the market, the white paper argues.
To further ensure the markets have clear outcomes, Kalshi is avoiding language saying that a trial will succeed or fail or show a “clinically meaningful” outcome, but instead will ask traders whether a study will meet its prespecified primary endpoint.
Given concerns that trading could influence how patients decide which trials they want to enroll in, Kalshi is listing markets for clinical trials only after enrollment has closed.
The paradox with these initial criteria is that even though they minimize certain risks, they also minimize the value of the markets in helping guide drug development decisions. By the time drugs are already in Phase 3 trials, drugmakers would have already committed significant amounts of money and time. The signals from prediction markets would be more meaningful for earlier-stage trials and for helping to determine whether a drug can make a clinical difference rather than just meet an endpoint.
Kalshi and AppliedXL acknowledge this paradox, saying in the white paper that the same criteria that make markets trustworthy also bias the exchange “toward programs that are already well-funded and well-covered, and away from the high-need, high-uncertainty research that most needs external signal.”
That’s why Kalshi’s goal is to eventually move into those high-uncertainty programs.
Lingering risks
Some researchers are still concerned about insider trading and manipulation. Most of these issues are discovered retroactively, so if regulators do discover any instances, the integrity of the trial may have already been affected, said Nicholas Zaorsky, a professor of radiation oncology at the Mayo Clinic who has been involved in many trials.
He said insider trading is a risk not only for people overseeing trials broadly, but even for those who play a smaller role, like doctors or nurses. They may see a subset of patients and place bets based on what they’ve seen.
Market movements could then also influence how patients or researchers behave, Zaorsky said. For example, patients can choose to drop out of trials at any point. As for investigators, the markets could influence how they record or interpret results, particularly for outcomes that are not objective, such as cognition tests for Alzheimer’s disease or depression tests.
“The main purpose of the trial is information-seeking. We are trying to find truth, and we’re trying to advance medicine,” Zaorsky said. “Once you start to introduce all these other incentives, that main objective goes out the window.”
Others see potential. Anne Wojcicki, the CEO of the 23andMe Research Institute, who has discussed the topic with Kalshi, acknowledged that there are ethical questions but said that ultimately prediction markets can help patients follow trials relevant to their disease and understand where the exciting science may be headed.
“It’s very patient-empowering,” she said.
Do predictions help science?
Another question Kimmelman grapples with is how valuable the markets will be in providing signals, given that research is inherently unpredictable.
“By definition, when you’re doing research, you don’t know what the results are,” said Kimmelman, whose work has shown that it’s actually quite hard to predict the outcome of trials. So the implication is that “these prediction markets shouldn’t give us very good signals. If they are, it is telling us something bad about our research environment,” he said.
Kimmelman is also concerned that prediction markets may drive greater conformity, reinforcing interest in already well-known drug targets or mechanisms, potentially leading to less investment in lesser-known areas that aren’t trading well in the markets.
“What’s most valuable for the patients in terms of major advances are underserved by that drive towards conformity,” he said.
Kalshi, however, argues that prediction markets are a way to bring in diverse opinions and surface contrarian thoughts. Also, the bigger the markets become, the more interest they can draw in from people who weren’t originally looking at clinical trials, according to Nicole Kagan, who writes market contracts at Kalshi.
She said there is “this reflexive impact where people are more likely to seek out this information and participate in these markets because they become salient and interesting to them.”
Editor’s note: The story was updated to note that STAT’s owner previously invested in AppliedXL.