Frequently asked questions

TargetMind is a multi-agent AI system for therapeutic target discovery. It emulates a target review board: independent domain-expert agents investigate a disease, debate conflicting evidence and reach an evidence-gap-guided consensus before prioritizing targets.

A general-purpose model follows a single linear chain of reasoning. TargetMind separates the work across independent experts with direct access to biomedical tools and databases, makes them cross-examine each other, and explicitly diagnoses and investigates evidence gaps before a decision is made.

Workspaces are anchored to diseases from the OpenTargets ontology search (EFO / MONDO identifiers), so you can start from any disease indexed there.

Yes. TargetMind's predictions have been experimentally validated in three disease systems — renal fibrosis, polycystic kidney disease and hypertrophic cardiomyopathy — with very high accuracy. Any new prediction is still a hypothesis that requires experimental validation.

The paper has not been released yet. A citation will be provided as soon as it is published.