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Kalshi recently announced that it will offer gambling opportunities to bet on whether the FDA will approve individual drugs as reasonably safe and effective. Betters will also be able to wager on whether the critical clinical trials that back those approvals succeed in meeting their primary targets (which is individually known as a primary endpoint).
But contrary to the company’s claims of better informing drug developers, patients, and researchers, creating a direct way to bet on drug trials and approval decisions will accomplish none of these goals. It will enrich Kalshi and likely a very small subset of bettors, while leaving most bettors poorer and, more importantly, introducing dangerous incentives that harm public health.
Officially, Kalshi is what is known as a “prediction market,” and the company – along with other “prediction markets” like Polymarket – refute the idea that they are gambling platforms. Unlike a traditional casino or form of online gambling, bettors do not wager against the house, meaning the company itself. Instead, Kalshi’s market hosts contracts between users who bet against one another. The company makes money from the volume of contracts and betting through fees rather than directly off of bettors’ losses.
Consequently, “prediction markets” like Kalshi and Polymarket are not regulated like online gambling platforms – namely sports betting — like DraftKings, Caesars Entertainment, FanDuel, etc. Online gambling is regulated at the state level, while “prediction markets” are federally regulated by the Commodity Futures Trading Commission (CFTC). Another key difference is that prediction markets are available to 18-21 year olds while online gambling is generally restricted to adults above the age of twenty-one. Additionally, online gambling faces a much harsher tax burden. This is especially true after the One Big Beautiful Bill Act, which made it so that someone who both won $100 and lost $100 would have to pay taxes on 10 percent of the winnings (meaning a loss of money when no money was won gambling).
Regardless of what official label is applied to Kalshi and regardless of the fact that it is regulated federally, there is no reasonable or logical way to argue that it is not gambling. “Prediction markets” are quite literally places where people place bets trying to predict the outcomes of events. Whether or not the company makes money as the house or by collecting transaction fees, it is still making money off of gambling.
The ridiculousness does not end with corporate talking points that argue “prediction markets” are not gambling, as Kalshi’s defense of entering the drug gambling business is no less asinine. Unfortunately, Kalshi’s move to profit off of betting on FDA approvals and clinical trials is also very dangerous to public health.
Contrary to the company’s claims, drug gambling is solely a money grab and opportunity for corruption rather than a benefit to society. Gambling on whether a clinical trial succeeds or the FDA approves a drug in no way makes a particular drug more beneficial or safe; it does not make drugs more affordable; it does not make people healthier. There is no tangible benefit to society other than enriching a gambling company that pretends it’s not a gambling company, Kalshi, and allowing anyone with the luck, skill, or potentially insider knowledge to profit from placing successful bets.
As a result, the existence of any negative impacts on health care and public health would clearly demonstrate the net-negative danger of the drug gambling that Kalshi is furthering.
Corruption and Insider Trading
Along with their announcement, Kalshi released a forty-four-page paper outlining their argument in favor and overall assessment of drug gambling. A primary argument that the company makes is that prediction markets can serve as more effective ways for outside observers, namely bettors, to guess the outcome of clinical trials and FDA approval decisions.
The main example of a successful “prediction market” that Kalshi offers at the beginning of their paper is quite literally an internal market that Eli Lilly ran with its employees in the early 2000s. Around 50 of its employees were able to more accurately guess the outcomes of clinical trials than corporate management. Yet, all this example shows is that people inherently with some form of insider knowledge whether directly or indirectly were able to place successful bets. This example does not highlight a shining beacon of gambling success as much as it confirms that inside information helps people bet. Even if the Eli Lilly case were a good example, it still reveals no benefit to society or public health, just a benefit to gamblers.
However, the risk of corruption and insider trading is significant given statements by industry leaders, the nature of the drug development and FDA approval processes.
Speaking on “prediction markets,” according to CEO of Robinhood Vlad Tenev:
I like to think about prediction markets as the next generation of the news … if you get the news before it happens, that should be even more economically valuable [than standard news]. So … it’s easy to just kind of lump it in with gambling, but this is a liquid market that gives people information in real time. I think there’s a ton of economic value in that.
Tenev’s comments beg the question: how does one get news information before it happens or becomes publicly available? Logically, the only way that prediction markets would show real news information that is not solely gambling guesswork is if there is insider trading involved. Only people with inside information have access to the news before it goes public.
This reality has not just been addressed indirectly. CoinBase CEO Brian Armstong revealed last year:
I actually had a real interesting conversation with one of the folks who was nominated to be CFTC commissioner about this [insider trading], and he asked me ‘do you think we should allow insider trading in prediction markets?’ And, I said it’s … not a clear-cut question right, because if your goal is to actually — for the 99 percent of people trying to get signal about what is going to happen in the world, like is the Suez Canal going to reopened or whatever — you actually want insider trading … Now, if you want to preserve the integrity of those markets, maybe you don’t want insider trading.
On 60 Minutes, Anderson Cooper told Polymarket CEO Shayne Coplan, “but, predictive markets do rely on someone having some inside information.” Coplan’s response was:
Yeah, I think that people going and having an edge to the market is a good thing. Obviously, you need to curate them and you need to be really clear and stringent on where the line is drawn … but it is sort of an inevitability that this will happen and there’s a lot of benefits from it. And, you know, people will adapt.
The Kalshi white paper attempts to argue against the idea of a serious insider trading concern by pointing to the fact that it is illegal and not permitted by the prediction market’s own tools. However, the strength of that argument relies on government and corporate oversight and enforcement being sufficient to overcome the “inevitability” (as Coplan put it) and incentives for insider information to drive some gambling behavior.
To prevent insider trading on a bet about whether a clinical trial will meet its primary endpoint, the company said it would ban people with trial-wide visibility, such as the lead investigator. However, individuals with less official visibility of trial results – like a site coordinator in a trial who only sees a small fraction of the total number of enrolled participants – are not. Additionally, there is always the possibility that people who are colleagues, friends, family, acquaintances, or any other relationship relating to someone with insider knowledge can make bets based on learning about such insider information.
Indirect insider trading can be particularly corrupting when it comes to knowledge held by government officials. Reviewers and leaders in the FDA along with other members of the federal government with interest and access to privileged information on drug approvals are now valuable sources of insider information.
There have already been legal cases against government employees engaging in insider trading, revealing both the corrupting incentives of these “prediction markets” along with the weaknesses of enforcement. For example, the Department of Justice (DOJ) charged Master Sergeant Gannon Ken Van Dyke in April with using insider information to make more than $400,000 in profits on Polymarket bets relating to the US capture of Venezuelan president Nicolas Maduro.
However, this legal action is not indicative of robust regulation, as this individual is amongst many more cases of betting on “prediction markets” prior to major government actions that have not seen legal consequences. In May, The New York Times reported that at least seven Polymarket users placed bets within hours of President Trump announcing a cease-fire agreement with Iran in early April, resulting in winnings of over $1.4 million, over $800,000 of which went to two individuals. Surges in betting activity prior to military actions have not just been reported on by news outlets; the Congressional Research Service (CRS) has documented this reality as well.
Importantly, these cases involve incredibly large amounts of money regarding major world events. Scrutiny on smaller winnings for smaller events – such as individual clinical trials and FDA approval decisions – may be less intense.
Furthermore, the question of legality and insider trading on prediction markets is not one hundred percent clear. The CRS has noted several different potential sources that could cover “prediction market” insider trading, but notes that “[t]he application of insider trading law to prediction markets raises several issues” relating to which rules are applicable. There have even been cases where the CFTC has not taken legal action against individuals when Kalshi imposed its own financial penalties, such as one instance where a political candidate traded on his own candidacy. While violating Kalshi’s internal rules, the CFTC has only noted that the candidate “potentially violated” the law. Such legal ambiguity leaves room for individuals to potentially get away with gambling based on insider knowledge.
Surveillance and enforcement against such corruption is additionally questionable given the current administration’s significant ties to “prediction markets.” Last year, Kalshi named the president’s son, Donald Trump Jr., as a strategic advisor, awarding him equity in the company worth reportedly $300,000 at the time, but now likely worth millions. Trump Jr. also sits on the advisory board for Polymarket.
In 2025, the Trump Media and Technology Group announced that it would create its own “prediction market” called Truth Predict. Since then, it has scaled back this project, instead announcing a collaboration with an already existing prediction market platform: OG.com.
President Trump and his administration have demonstrated considerable support for the industry in its battle to avoid regulation by the states. In a May 2025 Truth Social post, President Trump wrote:
It is critically important that the CFTC’s exclusive authority over Prediction Markets is maintained, and that they will thrive. Under my leadership, we are setting “rules of the road” that are the Gold Standard for the States. We cannot have SCUM like Chris Christie, Letitia James, Tim Walz, and JB Pritzker setting the rules! Other Countries are after this new form of Financial Market, and we want to remain at the top.
Relatedly, the administration’s CFTC instructed Kalshi to ignore an order from a Michigan court that instructed it to stop offering contracts involving sports events. The state attorney general, Dana Nessel, had sued Kalshi for violating the Michigan Lawful Sports Betting Act. While Kalshi complied with the court order, the CFTC told the company to go against the order by not canceling pending sports trades in Michigan.
Research and FDA Integrity
While insider trading is illegal primarily for the reason that it is unfair to investors in the general market, it carries much more dangerous risks in drug research and development. The introduction of gambling creates a money-making incentive that can corrupt the integrity of medical research itself.
It is already very well established in various studies and case studies that the clinical trials backing FDA approvals of drugs are heavily biased: a phenomenon called industry sponsorship bias. The FDA approves drugs not based on its own assessment, but based on the results presented by trials designed and conducted de facto by industry. Thus, these trials are known to be significantly more likely to have industry favorable conclusions than independent studies.
There are a myriad of ways for industry bias to corrupt the results of studies. Numerous design flaws can increase the chances of a favorable result for a company’s drug, such as choosing an unrepresentative patient population, adjusting dosage levels, choosing a poor comparator against the drug in question, and much more.
Additionally, slight adjustments to statistical analyses can make the difference as to whether a difference in a trial – such as if a drug improves overall survival – is statistically significant. For Kalshi’s drug gambling scheme, this point is significant because the clinical trial betting contracts are not about whether a trial shows a clinically beneficial outcome, but whether a trial meets its primary endpoint in a statistically significant manner. For example, a drug trial could theoretically show a statistically significant benefit in overall survival, but the benefit is so small (such as a few days of extra life) that it is clinically insignificant.
Now, the ability for people to make direct bets on whether a clinical trial meets its primary endpoint can introduce a significant incentive for those involved in trials in any capacity to bias how a trial is run or analyzed. This effect need not be large, as the alteration of even the slightest of results can be the deciding factor of whether a trial result is statistically significant or not.
This issue stretches beyond clinical trials and towards the FDA as well. On page 33 of the Kalshi white paper, the company makes a disturbing point:
On the informational side, prices on specific regulatory outcomes provide a more granular read on how public information is being interpreted than biotech stock prices alone. A market on a specific NDA approval that drops from 85% to 40% the day after an advisory committee briefing document is published is signaling something specific about how that document is being read, a signal available to anyone who checks the price, including the regulators whose decisions the market is pricing [emphasis added].
Kalshi itself makes the point that prediction markets can attract the attention of the very regulators who are making decisions on a particular drug. This additionally increases the potential for compromised regulators making regulatory decisions with corrupt motives.
An already well established phenomenon is the revolving door at the FDA, which has compromised the integrity of regulators. The promises of significantly higher-paying jobs in industry has – at the very least – given the appearance of corruption. In a June 2018 report to Congress, then-FDA commissioner Scott Gottlieb – himself a creature of the revolving door — wrote, “[FDA] employees are … attractive to industry and other private entities, which are sometimes able to attract such employees … with higher salary and benefit packages.”
An infamous example is the FDA’s approval of OxyContin. FDA reviewer Curtis Wright recommended approval of the drug even though Purdue Pharma had only submitted one study to prove efficacy that was “adequate and well-controlled,” and this trial lasted just two weeks. The FDA-approved label for the drug made claims that were not supported by trial evidence, such as that the drug “delayed absorption” was less subject to abuse. Wright would leave the FDA two years later to join Purdue Pharma, along with another key reviewer.
Thus, on top of the potential for a regulator to directly profit off a bet themselves or through an acquaintance, even the ability to profit from other people who could later employ them is a major corrupting influence. This is especially relevant given that the government has extremely limited revolving-door laws in Section 207 of Title 18 of the United States Code. This section includes restrictions to a former government employee’s direct lobbying activities for only a temporary amount of time, except for a lifetime ban on lobbying on “matters they were personally and substantially involved in.” Yet, none of these restrictions ban “behind-the-scenes” aid, so former employees can immediately advise the lobbying activities of companies as long as they don’t directly appear in front of or communicate with particular government officials themselves.
Transparency
Kalshi argues that its gambling scheme will enhance transparency to the benefit of not just investors, but drug companies, patients, and researchers alike. Like the company’s other claims, this one is baseless.
Again, without the presence of insider information, a “prediction market” does not present the news or any guaranteed transparent information on what drug trials will succeed or whether the FDA will approve a drug. Thus, the only “transparency” offered is the ability for the public to see what wagers people who think it is worthwhile to gamble are making.
Thus, when Kalshi argues in its white paper that drug gambling in its “prediction market” can “inform better capital allocation” for drug development, the company is grasping at straws to justify its new venture’s existence. More specifically, the company argues that a noticeable difference in how a company internally estimates the success of its drug development spending compared to what the gamblers believe on the “prediction market” would “warrant reexamination before additional capital is committed.”
This analysis is foolhardy on multiple fronts. Again – barring insider trading – the activity of bettors in no way reflects actual news on drug quality, clinical trials, or FDA approval decisions. Additionally, “prediction markets” don’t relate to the actual interests of pharmaceutical company research and development (R&D): establishing and expanding patent monopolies.
Unfortunately for the sake of public health, much pharmaceutical R&D is based on delaying competition rather than genuinely beneficial innovation. From 2005 to 2015, 78 percent of drugs associated with new patents were not actually novel treatments; rather they were existing drugs with slight, less clinically significant adjustments to extend the length of patent monopolies and prevent generic competition. According to corporate documents, in 2015, AbbVie documented its “defense strategy” to protect its patent monopoly for its drug Humira against competition from biosimilars that involved raising “barriers to competitor ability to replicate.” While the FDA approved Humira in 2002, the company filed 122 patents from 2014 onward. The idea that AbbVie and other drug companies would benefit from gambling activity on “prediction markets” about specific clinical trials or approval decisions in no way relates to reality and their actual profit-maximizing strategy.
Beyond drug companies, Kalshi also argues that “[p]atients and patient communities tracking drugs in development, particularly in rare disease” would benefit from increased awareness of promising treatments. The company points to the fact that, historically, patients have to rely on “one primary information source: the sponsor, whose press releases and investor materials are built to support confidence and tend to underreport negative or ambiguous results.”
This is very true. Pharmaceutical companies have control over the data from their clinical trials, posting only limited results on trial registries. They share limited data with medical journals when seeking to get their manuscripts published. There is also a well-documented history of selective publication, where drugmakers do not try to publish unfavorable trial results in journals, which are the gold-standard sources of medical information for doctors.
However, the idea that the unreliable spending habits of gamblers would, in any way, provide meaningful information on promising treatments to patients is beyond unsupported. Critically, this justification for drug gambling distracts from the actual policy solutions that can help patients have access to better data on new treatments.
The FDA currently has the authority to publicly release the underlying clinical trial data – including clinical study reports and de-identified individual participant data – that are necessary to truly vet and understand the results of industry-sponsored clinical trials. This transparency would allow researchers to vet the claims of industry and inform doctors and their patients on what benefits and harms were actually shown in a clinical trial along with any uncertainties due to trial design and/or conduct. Congress can also mandate such transparency, so that the FDA cannot decide not to release this information, especially across different presidential administrations.
Ultimately, Kalshi’s move to provide gamblers with the ability to bet on clinical trials and FDA approval decisions for drugs provides no tangible benefit to public health or society at large. It only serves to enrich Kalshi and a handful of bettors who are not producing any goods or services, but who instead happen to make successful bets. At the same time, drug gambling creates dangerous opportunities for insider trading – deemed a feature and not a bug by “prediction market” leaders – and corruption. These perverse incentives go beyond simple enrichment, as they can further degrade the integrity of medical research and regulatory decisions. Kalshi’s claims about enhanced transparency are completely unsubstantiated, and merely reflect a far-fetched attempt at justifying its profit-making scheme in the face of threatening the integrity of drug research and public health.
This first appeared on CEPR.
