The CNS-3D technology enables a reproducible model of Rett Syndrome (RTT) that captures functionally relevant phenotypes, evidenced by distinct electrophysiological signatures differentiating disease and control organoids. Its high reproducibility allows for reliable, rapid screening with minimal replicates, supporting throughputs of up to 20,000 samples per day.

Using a targeted compound library, the platform applies Analytix to perform high-throughput rescue ranking and generate detailed mechanistic insights based on neural network activity. This approach differentiates compounds with meaningful therapeutic potential from those with limited efficacy or adverse toxicity, with HDAC and AChE inhibition emerging as particularly promising pathways.