Biopharma's Public Probability

In 2003, Eli Lilly asked roughly 50 chemists, biologists, and project managers to trade shares tied to six drug candidates. The market correctly picked the three that would go on to succeed. The experiment stayed internal, but two decades later, public prediction markets are testing the same idea at scale.

The report explores what happens when expectations about clinical trials and FDA decisions become publicly visible and financially traded. It draws on expert interviews, historical case studies, and a market outlook. It accompanies the Kalshi–AppliedXL partnership announcement bringing regulated prediction markets to biopharma.

Why this matters

Whether a trial hits its endpoints or the FDA approves a drug can determine the future of a program, a company, or an investment. Pharmaceutical companies, investment banks, and institutional investors routinely estimate these probabilities. Almost all of those estimates are proprietary, paywalled, or reserved for 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 isolates one clinical or regulatory question. The price it produces is a new public signal, and its value depends on liquidity, participation, contract design, and the independence of traders.

What the report covers

• The information gap: Why probability-of-success estimates are central to drug development yet inaccessible outside major institutions.
• The evidence: What the Eli Lilly experiment and other forecasting markets suggest about aggregating dispersed knowledge.
• The risks and safeguards: Insider trading, manipulation, patient harm, trial interference, and the controls designed to address them.
• Contract design: Why early markets should focus on late-stage trials, larger sponsors, clearly defined endpoints, and decisions tied to authoritative public documents.
• Practical applications: How investors, drug developers, physicians, journalists, and regulators can interpret public probabilities without treating them as medical advice or definitive forecasts.
• The resolution framework: How contracts handle mixed results, composite endpoints, protocol amendments, and conflicts between sponsor announcements and official records. For a worked example, see How a Fact Becomes a Settlement.

For the first time, the market's expectations about a drug's future are becoming a public record. This report is a field guide to reading it.