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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
The Long, Expensive Road of Clinical Trials

Why the Clock Runs for Years

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Look at the timeline as a whole first. Each phase is a separate study with its own start and end, and the bars get longer as you move right. Phase one is short because only a few dozen people are involved and the question is narrow: is this safe? Phase two takes longer because it needs a few hundred people and has to watch for signs of benefit. Phase three is the longest because it enrolls hundreds to thousands and compares the drug against the current standard of care. Now look at the cost band underneath. It does not grow evenly with time. The early phases are cheap; phase three carries most of the spending because it has the most people, the most sites, and the longest follow-up. That is the key point: the money is committed late, after years of work, which is why a late failure is so damaging. And notice what sets the length of each bar. It is not computing speed. It is how long it takes to enroll people, how long the drug must be taken before an effect appears, and how long it takes for enough clinical events to accumulate. Those are properties of human biology and disease, not of the design software.
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A clinical trial is not a single experiment but a sequence of studies, and each one has its own clock. Phase I asks whether the drug is safe in a small group, typically a few dozen people, and usually runs for several months to about a year. Phase II asks whether it shows signs of working, in a few hundred people, and typically takes one to two years. Phase III confirms benefit against the current standard of care in hundreds to thousands of people and commonly runs two to four years. Add the time to design the protocol, obtain ethics and regulatory clearance, recruit sites, and analyze results, and a single drug program routinely spans eight to twelve years from first human dose to approval.

Cost accumulates unevenly across that timeline. Early phases are comparatively cheap because they involve few participants and short follow-up. Phase III dominates the budget because it enrolls the most people, runs the longest, requires the most sites and staff, and carries the cost of manufacturing and monitoring at scale. This is why the financial risk of drug development is concentrated at the end: by the time the largest bills come due, the sponsor has already spent years and cannot easily walk away.

The reason the clock cannot simply be sped up is that the measurements are biological and clinical, not computational. A trial must wait for enough participants to be enrolled, for the drug to be taken long enough to show an effect, and for enough clinical events — recoveries, relapses, side effects — to accumulate before the result is statistically meaningful. No amount of computing power changes how long a human body takes to respond.

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