While people were placing bets on the World Cup Final, Kalshi announced that users can now also bet on clinical drug trials.
In July 2026, Kalshi, an online gambling website, launched a program that lets users put money on clinical trial results and FDA decisions.
Supposedly, these new markets could bring much-needed honesty to drug development and reveal what company announcements often hide: how much confidence people really have in a drug?
That is the promise. But the moment clinical trial results become subject to a gamble, harder questions appear:
Is betting really what the field is missing?
Could the odds influence the outcomes?
Should people be allowed to make money by predicting whether a medicine succeeds or fails?
Whatever is considered success or failure.
To answer them, we first need to understand why Kalshi says this is a good idea and why it could actually be troubling.
One drug, one bet
People have always bet on whether a drug will succeed or fail by investing in the company that makes it. If they think a medicine works, they invest in the company, hoping to earn a profit as it grows. If they think it will fail, they use financial deals that pay out if the company’s value crashes
Kalshi just stripped away the “company” part and lets people bet directly on the drug itself.
Some contracts include FDA decisions on anito-cel, a multiple myeloma treatment being developed by Gilead and Arcellx, and ivonescimab, Summit Therapeutics’ experimental lung cancer drug.
This is not presented as a casino game, of course. The casino has put on a lab coat and now calls itself an information system.
Why Kalshi says this is useful
Kalshi claims that these markets are not for entertainment. Their argument begins with a real problem: drug development is difficult to follow.
“Drug development is one of the most important and most information-constrained industries on earth,”
Kalshi CEO Tarek Mansour said in the company’s official announcement.
“The data that determines which drugs advance and which don’t is largely locked away from the people who need it most. Surfacing information is what Kalshi is for, and we are committed to doing it right: compliance-first, carefully scoped, and built for the long term.”
Information about new drugs is often spread across company announcements, trial registries, medical conferences, investor reports and scientific publications. Much of it is technical, incomplete or difficult for the public to understand.
Kalshi argues that a market price can bring these different pieces of information together. For example, if a “Yes” contract is trading at 70 cents, the market is roughly suggesting a 70% chance that the event will happen. Unlike a company press release, the prediction is made by people who lose money when they are wrong.
Supporters believe this could give patients, investors and researchers a clearer picture of how confident people are about a drug. It could also challenge pharmaceutical companies when their public statements appear much more positive than the available evidence.
There is some history behind the idea.
In 2003, Eli Lilly created a small internal market in which around 50 employees traded contracts linked to six drug candidates. The Kalshi and AppliedXL white paper says the market correctly identified the three candidates that later became the most successful.
Prediction markets could allow employees and experts to express doubts they would hesitate to raise in meetings. A scientist may privately believe that a project is weak but feel pressure not to challenge senior managers. A market can sometimes bring that hidden uncertainty into the open.
For investors, the contracts may also be more direct than buying shares in a pharmaceutical company. A company’s stock can rise or fall because of its finances, management, competitors or other products. A contract tied to one FDA decision focuses on a much narrower question.
That is the attractive version: more information, fewer polished corporate messages and a public number that changes as new evidence appears.
Then come the less attractive questions.
Are there really any “outsiders”?
One of the biggest concerns is the insiders.
The people who can make the best predictions are the same people who have confidential information about a clinical trial or FDA review.
Kalshi says everyone trading in the new program has to provide employment verification.
The company’s white paper says strict rules are needed for people such as FDA employees, trial investigators, pharmaceutical-company staff, data safety monitoring board members and workers at contract research organizations. These groups see information before it becomes public.
But the employment checks and self-declared information do not solve every problem. Clinical trials involve large networks of hospitals, laboratories, consultants, technology companies and subcontractors. Betters can get information from a former colleague, friend or family member without working directly on the trial.
A doctor at one trial site may not have access to the complete results but could notice unexpected side effects, patient withdrawals or unusually strong responses. Even partial information could be valuable when money is involved.
Employment verification can show where someone officially works. It cannot always show what that person knows.
So who exactly counts as an “outsider”?
Perhaps an “outsider” is simply an insider with a less obvious job title.
We have seen this film before
There are some memorable examples of people betting on Kalshi with unusually good information.
Remember George Santos?
The former congressman was under investigation for placing a bet that he would not attend Trump’s annual speech to Congress after publicly saying that he planned to be there. Santos later missed the event and blamed a delayed flight. He was basically betting on an outcome that depended on his own behaviour.
In another case, Trump’s longtime teleprompter operator, Gabriel Perez, came under federal investigation for betting on certain words that would appear in the President’s speeches.
A teleprompter operator, obviously, may have a better idea than the general public about what is written on the teleprompter.
These cases are different from clinical trials, but the basic problem is similar. The person with the most accurate information is someone who is not supposed to trade.
Betters win, what about patients?
There is another problem: clinical trials are more complicated than “Yes” or “No.”
A cancer study can meet its main endpoint without proving that patients live longer. A drug may shrink tumours or delay their growth while its effect on survival remains unclear. It may receive accelerated approval while further evidence is still required.
For a trader, the contract has been resolved successfully. For a patient, the most important questions may still be unanswered.
Kalshi says every contract will name the exact document and outcome used to settle the bet; for example, a registered trial endpoint, an FDA approval letter or an advisory committee vote. This reduces confusion between traders, but it does not ensure that the public understands what the result means medically.
A market price could also influence the event it is meant to predict.
Patients may lose confidence if traders give treatments poor odds. Investors may pull money from a company. Doctors may become less willing to discuss a trial. A very high prediction could cause the opposite problem, creating excitement before the evidence is ready.
Kalshi’s report itself says these prices must never be used as medical advice and that their effect on patients and trials still needs to be studied.
Wisdom of the crowd or the opinion of three rich people?
Prediction markets are often praised for collecting the “wisdom of the crowd”. That only works when there is actually a crowd.
If only a small group is involved, the result can be easily distorted. A wealthy person can make a very large investment on one outcome and suddenly change the displayed odds. The number may then look like the opinion of a large, informed crowd when it may mainly reflect the actions of one rich and confident trader.
This matters because percentages look official. A patient might see that a drug has a high chance of approval and assume experts have carefully examined all the evidence. In reality, the odds may have been pushed up by a few people with deep pockets or perhaps by someone who knows more than everyone else.
The number does not explain who is behind it, how much they know or why they believe the drug will succeed.
It simply appears on the screen, dressed like a scientific fact.
Information tool or gambling?
Kalshi says it is offering a way to predict important events, not a traditional betting service. Several US states disagree and have taken legal action against the company over its sports and political contracts.
The legal arguments may be complicated, but the question for the public is simple:
Does giving a bet a more professional name make it something else?
Maybe Kalshi is right that drug development needs more transparency. Patients should not have to depend only on company announcements that describe almost every new treatment as exciting and promising. A public prediction could expose doubt and show that not everyone believes the optimistic headlines.
But it also creates a new product from that uncertainty.
One person sees a possible cancer treatment. Another sees a 62-cent “Yes” contract.
Until Kalshi can stop wealthy traders from pushing the odds, prevent insiders from using private information and make sure patients do not confuse a bet with medical evidence, these predictions should be treated with caution, not as a public service.
When the subject is a possible lifesaving treatment, turning uncertainty into another way to profit is not innovative. It is ethically difficult to defend.
by Mariam Harutyunyan, Associate Editor, OncoDaily Magazine
Deputy Managing Editor, OncoDaily
and Elen Baloyan, Editor-in-chief, OncoDaily Magazine
Managing Editor, OncoDaily
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