The tool limitation
Conventional tools only see static targets
Small molecules, biologics, and existing modalities depend on pre-existing, detectable binding sites — leaving the majority of disease-driving proteins out of reach.
The validation problem
Induced Proximity discovery has been largely serendipitous
Even recent advances in accessing difficult target classes lack a systematic, generalizable framework — making success difficult to predict or reproduce.
The opportunity
Novel protein interactions remain unprogrammed
The ability to systematically discover and engineer functional protein interactions represents one of the largest untapped opportunities in modern therapeutics.
Our Platform
A new pharmacological approach,
made actionable by AI
Arcadus sits at the convergence of four fields that have each matured independently — and are only now powerful enough to combine. Together they make it possible to systematically engage a class of targets that has resisted every prior generation of therapeutics.
Artificial Intelligence
Proprietary models trained on curated biological datasets — purpose-built for target classes that conventional AI pipelines were not designed to handle.
Structural Biology
Atomic-resolution understanding of protein architecture — including surfaces, interfaces, and dynamic conformations invisible to earlier discovery methods.
Next-Gen Modalities
Therapeutics engineered for surface-level and interface biology — capable of engaging targets that small molecules cannot reach and biologics cannot penetrate.
Engineered Interactions
A framework that moves beyond classical occupancy and inhibition — working with cellular biology to achieve therapeutic outcomes at targets previously considered undruggable.
