Translational concordance auditor. Queries four public pharmacovigilance databases and classifies compounds into tissue trap zones on S³. Properties from PubChem. Quantum-computed properties available via mosaeQ.com/lab.
Enter a compound name to query concordance data across all four public safety databases.
LogP and TPSA are mapped to quaternion coordinates (θ, φ) on S³. On msq, these values are sourced from PubChem. For NEMP quantum-computed values from SMILES alone, use mosaeQ.com/lab. Natural pharmacological zones emerge on the hypersphere, identifying where drugs accumulate before clinical exposure.
The trap zones above use PubChem properties — precomputed, public, approximate.
mosaeQ.com/lab computes trap zone classification from NEMP quantum properties — deterministic, from SMILES alone, with P-gp efflux prediction, brain/plasma ratio, FAERS concordance, and opioid safety panel.
For novel compounds not in PubChem, quantum classification is the only option.
Run Quantum Classification → mosaeQ.comThe FDA’s openFDA API returns NOT_FOUND for clinically validated drugs never marketed in the United States.
In 2026, msq.mosaeQ.com discovered that the FDA’s openFDA API returns NOT_FOUND for clinically validated drugs that were never marketed in the United States — erasing decades of European clinical evidence from automated safety queries.
The FAERS Product Dictionary is built from Structured Product Labeling for “all marketed US drugs” (Potter et al., Clinical Pharmacology & Therapeutics, 2025; PMC12393772).
Any drug never US-marketed is invisible. We call this the Digital Cliff.
Click to see the FDA API return NOT_FOUND for a clinically validated 1957 drug.
A machine-readable rulebook for quantum-computed drug safety classification
The msq: ontology defines how molecular safety data is structured, classified, and queried across the mosaeQ platform. It receives computed property values from the quantum engine and classifies compounds into safety zones using formal logic. It connects to international regulatory formats used by EMA, FDA, and ECHA.
Three-layer separation: the engine computes, the ontology classifies, SPARQL queries.
v2.0.0 | April 2026 | OWL 2 DL | 39 classes | 87 properties | 11 SHACL shapes | 18 namespace alignments (ChEBI, MedDRA, NCIT, CDISC/SEND, ENVO, GO, OBI, SNOMED CT)
Qualifying researchers, regulatory scientists, and pharmaceutical professionals in health technology may apply for complimentary two-month access to the msq quantum ontology. Academic, government, and clinical applicants are prioritised.
Apply for Beta AccessIndividual and enterprise subscriptions available at mosaeQ.com for immediate full-platform access.