Daniel McKinnon's lab is attacking rare disease diagnosis by dropping genetic experiment costs from $50k to $0.50 per test. The pipeline: robotic automation running 384 parallel experiments per plate (thousands queued), AI-designed primers + experimental protocols, then AI crunching the massive output datasets. Target use case is mutation effect profiling in fetal lung cells. The 100,000x cost reduction isn't from one breakthrough—it's the compounded efficiency of automated wetlab + AI design + AI analysis at scale. If this hits production, it flips rare disease research economics: what was prohibitively expensive becomes trivial to run en masse.