Gordian uses AAV vectors to create a "mosaic" tissue where different cells receive different genetic perturbations. Single-cell transcriptomics then reveals the causal effects of each target in a complex, living environment, a massive speed advantage over traditional, single-target animal studies.
Inspired by the broad benefits of drugs like GLP-1s, Gordian is proactively creating "atlases" of target effects across multiple organs (heart, kidney, liver). This strategy positions them to discover the next class of drugs that treat multiple related conditions simultaneously, a key focus for their internal pipeline.
While AI excels where large, clean datasets exist (like protein folding), it struggles with modeling slow, progressive diseases like Alzheimer's or obesity. These are organ-level phenomena, and the necessary data doesn't exist yet. In vivo platforms are critical for generating this required foundational data.
Pharmaceutical companies like Pfizer have vast amounts of human genetic data (GWAS hits) linked to diseases but struggle to determine which are viable drug targets. Gordian's high-throughput in vivo screening directly tests the causal effects of hundreds of these targets, rapidly identifying the most promising candidates.