The Discovery Tsunami

For the last decade, the biotech industry has been obsessed with discovery. We have AlphaFold, CRISPR, and DNA-encoded libraries. We are drowning in potential drug targets. The faucet is wide open.

But downstream, the pipe is clogged. This is the Great Stagnation.

While we can simulate a molecule in seconds, moving that molecule into a human patient still takes 18 months of pushing PDFs back and forth until the heat death of the universe. This creates a bottleneck where brilliant science dies waiting for a Gantt chart from hell.

AGI-Augmented Pharma

WarpSpeedBio is built on a contrarian thesis: The hardest problems in pharma today are not biological; they are logistical and linguistic.

An IND filing is just a very specific arrangement of text. A clinical protocol is just a logical set of instructions. These are tasks that Large Language Models (LLMs) excel at—not just assisting with, but executing.

We are building the first pharmaceutical operator where the "operating system" is not a hierarchy of middle managers, but a swarm of autonomous agents. We don't just want to make drugs faster; we want to break Eroom's Law forever.