Prediction markets are expanding into an increasingly controversial area: clinical trials and drug approvals.

Platforms such as Kalshi and Polymarket now allow users to wager on whether experimental treatments will succeed in clinical trials. They can also bet on whether those treatments will receive approval from the U.S. Food and Drug Administration. Supporters argue that these markets can generate useful information about the likelihood of medical breakthroughs. Meanwhile, critics say betting on the success or failure of treatments raises serious ethical concerns. This is because real patients are directly affected by the outcomes.

Why Clinical Trial Betting Is Drawing Criticism

For families whose lives depend on experimental treatments, the idea of people making money from a clinical trial’s failure can feel deeply disturbing.

Boston University professor Joshua Pederson became particularly concerned after his son, who was diagnosed with cancer, entered a clinical trial. This was following the return of his disease.

Pederson argues that prediction markets can make people forget that behind every clinical trial are patients facing serious medical conditions.

A failed clinical trial is not simply a financial event. Instead, it can mean that patients lose access to a potential treatment. It can also mean that researchers abandon a therapy that could otherwise have helped future patients.

How Prediction Markets Work

Prediction markets allow participants to buy and sell contracts based on the likelihood of future events.

Users can potentially make money if their predictions are correct.

Kalshi has expanded this model beyond traditional political and economic events and into biotechnology and pharmaceuticals. Users can currently trade contracts related to whether certain medications will receive FDA approval and when regulatory decisions could occur.

Polymarket has also offered markets related to pharmaceutical approvals and other biotechnology questions.

The companies argue that these markets can provide a new source of information. They do this by aggregating the expectations of thousands of participants.

Kalshi Says Prediction Markets Could Help Medical Research

Kalshi argues that betting markets could provide useful signals to investors and researchers. These signals show which treatments appear more likely to succeed.

The company has also argued that financial markets already allow investors to profit from companies whose clinical programs fail. So, prediction markets are different primarily in how they organize and present that information.

Kalshi says its markets can create an open dataset showing how participants assess the probability of clinical and regulatory outcomes.

The company has also introduced safeguards intended to reduce insider trading, including employment verification and monitoring for unusual trading activity.

Researchers Warn About Trial Integrity

Some medical researchers remain unconvinced.

David Tsai, a clinical trial researcher at a biotechnology company in California, has argued that prediction markets could create financial incentives. These incentives could lead people involved in trials to influence outcomes.

Clinical trials involve numerous people and variables, including researchers, physicians, pharmacists, coordinators and other professionals. Critics worry that someone with access to confidential information could potentially use that knowledge to make profitable trades.

There is also concern that a person involved in a study could deliberately manipulate a trial. This could happen if they had a financial interest in a particular outcome.

Radiation oncologist Nicholas Zaorsky has similarly warned that clinical trials are fundamentally different from many other prediction-market subjects. This is because the people involved can sometimes influence the outcomes being predicted.

The Insider Trading Problem

Prediction markets also raise questions about access to confidential information.

Clinical trials generate sensitive information long before results become public. Researchers, pharmaceutical executives, physicians and trial participants may have knowledge that ordinary investors do not.

Kalshi says its safeguards are designed to identify and prevent inappropriate trading based on insider information.

The company also points to cases in which prediction markets have helped identify suspicious trading activity in other areas.

However, critics argue that monitoring unusual activity after a trade occurs may not be enough to prevent every possible attempt to manipulate a clinical trial. It may also not be enough to stop profit from confidential information.

Patients Are at the Center of the Debate

The strongest criticism is not necessarily about gambling itself. It is about what is being wagered on.

Election results, sports games and economic indicators can have consequences. However, clinical trials involve people whose health and lives may depend on the outcome.

Pederson argues that prediction-market platforms can make those human consequences feel distant. This happens because users interact with the information through numbers, contracts and financial incentives.

For patients and their families, however, those outcomes are anything but abstract.

A successful clinical trial could create another treatment option. A failed trial could mean years of research end without producing a viable therapy.

What Kalshi and Polymarket Say

Kalshi maintains that its biotechnology markets can improve transparency and provide useful information about medical innovation.

The company has also said it focuses on late-stage clinical trials. It does not allow markets involving trials in which all participants are minors.

The platform argues that information generated through prediction markets could potentially help investors identify promising treatments. It could also encourage funding for medical research.

Polymarket, meanwhile, has offered markets involving FDA decisions and pharmaceutical developments but declined to comment on the controversy.

Could Prediction Markets Influence Medical Decisions?

The debate ultimately raises a difficult question: Can financial incentives coexist with the scientific integrity of clinical research?

Prediction markets are designed to reward accurate predictions. Clinical trials, however, are designed to determine whether a treatment works safely and effectively.

Those objectives can potentially collide when people with access to sensitive information have something financially at stake.

Researchers therefore face the challenge of protecting the integrity of clinical trials. At the same time, they must ensure that new sources of information do not create additional risks for patients.

The Ethical Debate Is Just Beginning

The controversy surrounding Kalshi and Polymarket reflects a broader debate about how far prediction markets should expand.

These platforms have already moved beyond traditional financial forecasting into politics, entertainment, international conflicts and other areas of public interest.

Clinical research may represent one of their most sensitive frontiers.

Supporters see prediction markets as sophisticated information-aggregation tools that could reveal valuable insights about medical innovation.

Critics see something fundamentally different: a financial system in which people can profit from outcomes that determine whether seriously ill patients gain or lose another potential treatment.

As prediction markets continue to grow, regulators, researchers and patients will increasingly have to decide where the line should be drawn between valuable forecasting and betting on human suffering.