Biopharma's Public Probability
A new report from Kalshi and AppliedXL examines the state and future of prediction markets in drug development, and what happens when expectations about clinical and regulatory success become publicly visible.
In 2003, Eli Lilly asked roughly 50 chemists, biologists, and project managers to trade shares tied to six drug candidates. The internal market identified the three candidates that would go on to become the most successful.
The experiment remained limited in scope, but it offered an early example of how markets could surface knowledge dispersed across an organization, including views that may not emerge through conventional forecasting and decision-making.
Two decades later, public prediction markets are testing a related idea in a different setting.
Biopharma's Public Probability examines what happens when expectations about clinical trials and FDA decisions become publicly visible and financially traded. Drawing on expert interviews, historical case studies, and an outlook for how the market may develop, the report explores the information these markets can produce, the risks they raise, and the standards required for them to function responsibly.
The report accompanies the launch of the Kalshi and AppliedXL partnership bringing regulated prediction markets to biopharma; the first markets are live on Kalshi.
Why this matters
Whether a clinical trial meets its endpoints or the FDA approves a drug can determine the future of a development program, a company, or an investment.
Pharmaceutical companies, investment banks, institutional investors, and researchers routinely estimate the probability of these outcomes. Most of those estimates remain proprietary, paywalled, or available primarily to organizations with substantial research resources.
Prediction markets create a continuously updated public price tied to a defined event:
- Will a Phase 3 trial meet its prespecified primary endpoint?
- Will the FDA approve a particular drug for a specified indication by a certain date?
Unlike a biotech stock, which reflects the prospects of an entire company, a prediction-market contract focuses on a single clinical or regulatory question.
The resulting price is a market-implied probability, not a scientific conclusion or definitive forecast. Its usefulness depends on liquidity, participation, information quality, contract design, and the independence of traders.
What the report covers
- The information gap: Why probability-of-success estimates are central to drug development and investment decisions, yet remain inaccessible outside major institutions.
- The evidence: What the Eli Lilly experiment and other forecasting markets suggest about aggregating knowledge dispersed across organizations and participants, along with the limits of that evidence.
- Risks and safeguards: The ethical and practical concerns raised by biopharma prediction markets, including insider trading, manipulation, effects on patient enrollment, potential harm to vulnerable populations, and the possibility that market prices could be mistaken for medical or scientific evidence. The report also examines safeguards intended to reduce those risks while recognizing that they cannot be eliminated entirely.
- Contract design: Why early markets may be better suited to selected late-stage trials and regulatory decisions with clearly defined endpoints, reliable disclosure windows, and authoritative public sources.
- Practical applications: How investors, drug developers, physicians, journalists, researchers, and regulators may interpret public probabilities without treating them as medical advice, scientific consensus, or definitive forecasts.
- The resolution framework: How contracts can address mixed results, composite endpoints, protocol amendments, publication timing, and conflicts between company announcements and official records. For a worked example, see How a Fact Becomes a Settlement.
A new public signal
For the first time, market expectations about selected clinical and regulatory outcomes are becoming broadly visible through regulated, publicly traded contracts.
Biopharma's Public Probability is a guide to understanding that signal, including what it may reveal, where it can mislead, and what standards are needed for it to develop responsibly.
AppliedXL does not provide investment, legal, or medical advice. This material is provided for informational purposes only and is not a recommendation to trade any contract or security or make any medical decision.