One day in early May, web-based prediction market platform Kalshi listed two contracts tied to Compass Pathways’ psilocybin drug, COMP360. Patrons could wager on when the company would submit a new drug application for treatment-resistant depression and post-traumatic stress disorder or when the FDA would approve the drug, with several timing choices offering different payouts.
Kalshi refers to offerings like these as “event contracts,” terminology commonly used in prediction markets. Users can see how much money is flowing into a contract, the implied probability of an event occurring and the potential payouts.
These markets have taken the U.S. by storm in recent years, with AI crawling public data and offering opportunities to bet on everything from sports games to speculative questions about extraterrestrial life. The rise of these prediction platforms, and the geopolitical nature of some of the events that can be traded on, have drawn plenty of scrutiny and criticism.
NBC News reported last month that there have been $2 billion in wagers connected to the war in Iran on cryptocurrency prediction market Polymarket, with several large bets preceding military strikes or ceasefires, leading to questions about insider knowledge. A U.S. soldier was arrested and charged for using classified information to win $400,000 on a contract about the raid on the home of Venezuelan President Nicolás Maduro.
The growth of prediction markets creates new challenges for regulators. Insider trading is already difficult for the Securities and Exchange Commission to detect in traditional financial markets. A University of Technology Sydney study found that only around 15% of insider trading in the U.S. is uncovered by the SEC.
Prediction markets, meanwhile, largely fall under the jurisdiction of the Commodity Futures Trading Commission (CFTC), a smaller agency with oversight limited to primarily U.S.-based platforms.
Now, prediction markets have come to the biotech world. Several biotech contracts are rotating through Kalshi and Polymarket, while a recently launched clinical trial prediction market called Endpoint Arena has also entered the scene.
Endpoint Arena is still in pilot mode and currently only allows paper trading, meaning users can’t wager real money. The platform lists contracts tied to the likelihood of companies like Palisade Bio, argenx and Jazz Pharmaceuticals meeting endpoints in their ongoing trials.
The emergence of biotech-focused contracts is raising questions about whether prediction markets could eventually influence clinical trials and drug development rather than simply forecast them.
‘Speed up science’
Endpoint Arena CEO Michael Fischer, Ph.D., studied economics and computer science at Stanford and became curious about the promise of prediction markets after creating an app to share among his friends that synced up their sleep data from Apple Watches or Oura rings. That app allowed users to bet on and experiment with sleep quality based on food, bedtime and other variables.
“I became very interested in this concept of experimentation and encouraging other people to think about and place bets on what they think is going to happen if they do certain experiments,” Fischer told Fierce in an interview.
Prediction markets like Endpoint Arena provide an opportunity to take a position on a specific event within a company’s larger profile. Stocks move up and down based on multiple factors and data points, but prediction markets focus on a specific event like a drug approval or data readout rather than all the variables reflected in a biopharma company’s overall stock price.
Fischer argues that clinical trial-focused prediction markets can democratize the trial process and give participants motivation to become experts and improve experimentation.
“It creates a layer by which people could be incentivized to forecast the future, which can be beneficial to society and determine whether a drug is going to work or not,” Fischer said.
Online betting, gambling
Endpoint Arena currently focuses on phase 2 trials, which Fischer described as pivotal inflection points in drug development. He said the company’s AI model initially sets market odds using publicly available information, after which users can make their own predictions.
Fischer also made the bold claim that prediction markets could eventually provide scientific benefit. He offered a hypothetical example involving a known GLP-1 drug being studied in a new indication. If someone already taking the therapy for diabetes or obesity experienced improvements related to the new condition being evaluated in the trial, Fischer suggested they could use that firsthand experience to inform a prediction on the market.
In theory, he argued, patterns that emerge through those predictions could provide early signals about a drug’s potential in additional indications before formal trial results are released.
“One could do a more focused and targeted trial with fewer people,” he said. “It’s a way to speed up science and creates a market where one is incentivized to move quickly and use fewer resources in order to get to the outcome.”
Fischer also suggested that prediction markets could provide patients with another tool for evaluating whether to participate in a trial, alongside discussions with physicians.
“Patients should be informed of the risks and probability of success,” he said. “If a trial is going to end early because it doesn’t show promising results, that’s a good thing.”
Endpoint Arena is targeting a highly specialized biotech audience, and Fischer said the company is developing AI features that would allow users to run a virtual wet lab and request datasets to learn more about potential trials.
“Just as LinkedIn and Facebook have different tools and features and cater to different user types, we are going to see a lot more specialization in the prediction market space around different verticals,” he said.
‘Wild west situation’
As buzz about prediction markets has grown, they have drawn the attention of academics, who debate the impact of these platforms on society and the events they are predicting.
Barnard economics professor Rajiv Sethi, Ph.D., was first made aware of prediction markets more than 30 years ago and has been writing about and studying them ever since. He noted that these markets can be useful to society when dealing with unprecedented events. For example, during the COVID-19 pandemic, dozens of models predicting the spread of the disease lacked consensus.
“Closing the schools and beaches, mask mandates or distancing requirements can’t be incorporated into traditional prediction models, because those events are very specific to that particular pandemic,” Sethi told Fierce in an interview. “But a prediction market can take into account information from a broad range of sources, and that can be immensely socially valuable.”
But a primary worry among critics is how the existence of a prediction market for an individual event could affect the outcome of that event. While Sethi hasn’t dived into the biotech market specifically, he has examined how feedback loops between beliefs and actual probabilities can affect outcomes in prediction markets, especially in politics.
“What I believe about who’s going to win an election might affect voter turnout, fundraising, donations, morale and things that can actually affect the likelihood of someone winning,” he said.
In a similar vein, critics of clinical trial prediction markets question how beliefs about a trial could affect its eventual outcome. Melinda Chu, M.D., is a physician scientist and CEO of Ecotera Health, a biotech and sustainability company focused on industrial waste and human health challenges. She previously helped manage and coordinate dermatology and oncology clinical trials as a dermatologist and is concerned that seeing the odds on a trial could dissuade participants from signing up, which could affect the overall outcome if enrollment falls short.
“A smaller biotech that’s not public could face these headwinds that they can’t address in the same manner as if they were a larger company,” Chu told Fierce in an interview. “If they need 20 patients to enroll to meet the next milestone for funding [but] they can only enroll 16 people because of a prediction market—that’s where I see the potential problem.”
If there is money on the line for a trial’s outcome, those with power and skin in the game may be motivated to use social media to influence potential trial participants, Chu suggested.
“I see the potential for people being swayed by what they see on social media or a message board,” she said. “Adding in the gambling element, people will have motives to post more publicly about how a drug will fail, and it may discourage patients from considering a trial.”
There are also worries about the opportunity to use prediction markets to make money on biotech insider information.
“In a situation where you can win a lot of money with an accurate prediction regarding the outcome of a clinical trial, it’s an invitation to those with access to non-public information to compromise their integrity to make the money,” Michael Abrams, a managing partner at consulting firm Numerof, told Fierce.
“It’s a wild west situation, and I realize that enforcement would be a mammoth headache,” he added.
Abrams also warned of the impact these markets could have on smaller biotechs that already face hurdles in bringing treatments to market. The FDA’s recent move toward more transparency, with the release of complete response letters and criticisms of clinical trials, can already be difficult for companies to navigate, he pointed out.
“If you’re a startup, and you just ran your trial, and the FDA’s letter is out there in the press one morning when you wake up, how many investors do you have by noon?” Abrams said. “You mix that in with prediction markets, and people will want to bet on whether you’ll still be in existence by the end of the day.”
‘Always out of reach of regulators’
Regulation of these platforms themselves is another question. While the CFTC theoretically regulates prediction market contracts and prosecutes insider trading violations, the U.S. soldier who bet on the Venezuelan operation is the first and only person charged with insider trading in the prediction market space. Meanwhile, international crypto-based prediction markets like Polymarket are beyond U.S. regulators’ jurisdiction.
“This kind of market without any verification, now that cryptocurrencies are a big part of the global system, are going to be out of reach of regulators always,” economics professor Sethi said.
For now, the biotech corner of the prediction market space remains small. Less than $50,000 is currently being wagered across all biotech-related contracts on Kalshi combined, and Endpoint Arena has yet to move beyond paper trading.
But if these markets grow, they will likely attract the attention of professional investors who will be highly motivated.
Despite criticisms connected to insider information and its potential impact on the industry and trial outcomes, Fischer is sticking to his argument that the markets have the potential to motivate more science, improve transparency and draw more attention to the trial process, with the consequence of improving outcomes.
Sill, as Endpoint Arena’s profile grows, the responses have been as divided as the broader debate around prediction markets.
“One is that it’s the best thing ever; the other is that it’s the worst thing ever,” Fischer said. “The third response is that no one wants this, and the fourth is that everyone wants this.”
