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Why AI-Designed Drugs Haven't Changed Medicine Yet

1The Promise and the Puzzle2From Molecule to Medicine: The Journey a Drug Must Survive3Where AI Actually Helps in the Pipeline4The Prediction Gap: When a Good Molecule Meets a Real Body5The Long, Expensive Road of Clinical Trials6Money, Incentives, and the Business of Drug Development7Regulation, Evidence, and Trust8What Would Have to Change
Money, Incentives, and the Business of Drug Development

The funding filter: risk against expected return

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Think of this as a gate that every project has to pass, and then pass again. On one side is expected return — the size of the prize multiplied by the chance of reaching it. On the other side is risk — the money already spent and the chance of losing it. A project with a low chance of success only gets through if the payoff is large or the path is cheap. Watch how the gate is not passed once. It is re-applied at every stage, so a project that entered can still be stopped later when new evidence lowers its odds or raises its remaining cost.
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A company deciding whether to fund a drug project is not asking whether the science is interesting. It is asking whether the expected return justifies the risk. Expected return is the value of a success multiplied by the probability of reaching it. Risk is the chance of losing the money already committed, and the size of that loss.

A project with a high chance of success and a large market clears the filter easily. A project with a low chance of success needs either a much larger payoff or a much cheaper path to survive the same filter. This is why two scientifically similar candidates can receive opposite decisions: they differ in probability, in cost to the next decision point, and in how much the market would pay if they worked.

The filter is applied repeatedly, not once. At each stage the company can stop, continue, or sell the project, and the decision is remade with whatever new evidence has arrived. A candidate that looked worth funding at the start can be dropped later if the evidence lowers its probability of success or raises its remaining cost.

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