Kalshi and Polymarket Are Now Taking Bets on Clinical Trials. Researchers Say That Is a Structural Integrity Problem.
Kalshi and Polymarket have begun allowing users to bet on the outcomes of clinical drug trials and FDA approval decisions. Researchers running those trials say the markets create direct financial incentives for people with access to trial data — pharmacists, coordinators, investigators — to tamper with results. Kalshi argues the markets are no different from stock market short sellers and will provide valuable information about drug development. Critics call the whole thing 'ghastly.' The debate represents the most ethically serious challenge prediction markets have faced.
Kalshi currently accepts bets on whether a weight-loss drug and a breast cancer treatment will receive FDA approval, and on what date. Polymarket is taking wagers on the approval of cancer treatments and whether the United States will permit Chinese peptides to be sold to American consumers. Both platforms describe the markets as a way to generate new information about the drug development pipeline — Kalshi has published a white paper co-authored by Anne Wojcicki, the founder of genetic testing company 23andMe, arguing that open, transparent trial probability data could be 'extremely promising and empowering for people' who cannot otherwise access information about clinical options. Polymarket declined to comment.
Researchers who run clinical trials are not persuaded. David Tsai, who manages trials at a Bay Area biotech company, has started an online petition calling for the bets to be banned, arguing they 'threaten the very foundation of trust and integrity in biotechnology.' His concern is not abstract: prediction market payouts create a direct financial incentive for anyone with access to a trial — pharmacists, lab technicians, coordinators — to influence the outcome. 'A pharmacist who had placed a bet saying that it's going to work well, or doesn't work well, could obviously adjust the infusion rate, could adjust the source temperature of the drug,' Tsai told NPR. 'They could change any number of variables that could obviously have a direct impact on how the trial and the data and the patient safety would come out.' Nicholas Zaorsky, a radiation oncology professor at the Mayo Clinic who has helped run clinical trials, put the structural issue directly: 'Investigators, coordinators, and sometimes even participants can directly influence aspects of the outcomes being wagered on. That creates financial incentives that risk undermining trial integrity.'
Kalshi's response is that this risk already exists at scale in the stock market, and has for decades. Biotech short sellers profit from clinical trial failures; institutional investors with pharmaceutical sector exposure have much larger financial stakes in trial outcomes than any prediction market position. 'If you want to ban profiting from the failure of clinical trials, you would start with the stock market, where the financial incentive for this type of profit is orders of magnitude larger,' Kalshi spokesman Jack Such said. The argument has real force: a hedge fund with a short position in a pharmaceutical company has vastly more money on a trial outcome than a retail Kalshi user, and faces the same insider trading incentive. The difference the researchers point to is practical rather than principled: clinical trial investigators, coordinators, and pharmacists are not typically trading biotech equities, but they are exactly the people who might open a Kalshi account once the platform's marketing reaches them. Kalshi says it will verify employment data and surveil for unusual activity, the same tools it has used in other markets — but the Bloomberg investigation published in July, which identified $200 million in suspicious wagers across Kalshi and Polymarket through June 2026, documented in detail how those safeguards have been circumvented in financial event markets via fresh accounts and proxy structures.
The stakes are not abstract for the patients inside the trials. Joshua Pederson, a humanities professor at Boston University whose 12-year-old son is currently enrolled in a cancer clinical trial after a recurrence following initial chemotherapy and radiation, describes the framing as a category error. 'A clinical trial failing is a more sanitized euphemism for: people are going to suffer, people are going to die, people are going to have one fewer clinical option available to them in one of the most difficult medical situations of their entire life,' Pederson said. His objection is not only about tamper risk. It is about what it means to design a gamified system that pays users when that outcome occurs. 'One of the things that has struck me about these platforms is that they're flashy and they're gamified in such a way that you're often kind of distanced from the real cost,' he said. Pederson called the whole concept 'ghastly.' Kalshi has said it will restrict bets to late-stage trials where participants have already been enrolled, and will not offer markets where all trial subjects are minors — though the company acknowledged both of those limits could change.
The clinical trial debate is structurally different from the prediction markets controversies that preceded it. State gaming law preemption, Congressional scrutiny, the Group of Copenhagen's integrity report on World Cup markets, the Bloomberg insider trading investigation — each of those involved disputed legal authority, incomplete regulatory frameworks, or enforcement gaps. Clinical trial integrity is something else: the question of whether a market should exist at all, because its existence may degrade the thing being predicted. Prediction markets are usually defended on the ground that they aggregate dispersed information efficiently and without causing side effects. In liquid financial markets, that is a credible claim. In a clinical trial with thirty investigators, the information is not dispersed — it is held by a small, identifiable group of people who are now being asked to interact with a market on which they have private knowledge and direct influence over outcomes. Whether prediction market platforms can design around that structural problem, or whether Congress or the FDA will act before the question resolves itself, is now an open regulatory question with patients inside the answer.
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