BIOS can design a drug candidate in under an hour, for under $7. Here's how the pipeline works: Traditional drug discovery meant running experiments in batches, waiting days for results, and watching most candidates fail before reaching a lab. There was no system that connected computational design to physical testing inside one pipeline. BIOS now builds that. Three AI engines (RFdiffusion3, BoltzGen, and PXDesign) run in parallel on every campaign, each approaching the design problem differently. Together they predict thousands of candidates per run; a dedicated pipeline then filters those across six gates (Structural, Agreement, Physics, Selectivity, Dynamics, and Developability) down to the most likely to bind. Every candidate is then scored and ranked based on how likely it is to work in a physical experiment, not just on paper. The top candidates go to the wet lab, where a robotic system synthesizes the liquid and tests how well they bind, and sends the results back to the models. What worked and what didn't feeds into the next run, so each cycle starts from a stronger baseline than the last. Full breakdown and our vision for BIOS ↓

Science has never been short on good ideas. The real bottleneck has always been everything that comes after the idea. You still need funding, the right data, and lab time, and each of those steps comes with its own friction and delays. For funding, you need to wait for committee reviews. The specific dataset you need is often locked away by whoever controls it. Booking equipment usually means chasing the right person just to get it set up. Months can pass by before anything meaningful actually happens. Now agents are starting to break through those barriers. They can hold a budget and spend it as soon as it’s needed. Pull the data, secure the lab time, run the experiment, and immediately use the results to plan the next step. The whole loop is finally starting to move on its own.