Stress-test the target before you commit
A weakly-validated target survives to docking and wastes the whole run. NovoMCP challenges every hypothesis against clinical trials, measured bioactivity, and contradicting literature. The engine returns a confidence tier with the evidence on both sides, the case for the target and the case against it.
“Validate EGFR as a target for non-small cell lung cancer, and show me the contradicting evidence too.”
How it works
Name the target
Pass a gene or target from the discovery stage. The engine assembles every evidence stream it can find, clinical trials, ChEMBL bioactivity, literature, and the omics data.
Adversarial weighting
Evidence is combined with tiered weights: clinical trials 3×, ChEMBL bioactivity 2×, literature 1×, omics 1×. Failed trials and contradicting reports are surfaced in full, so a fragile hypothesis fails here instead of at docking.
A confidence tier, with caveats
You receive a tiered confidence assessment and the specific evidence behind it, supporting and contradicting, so the decision to spend compute is made with eyes open.
Proof
validate_target stress-tests each hit with tiered weighting: clinical trials (3×), ChEMBL bioactivity (2×), literature (1×), omics (1×).
Cross-checked against search_clinical_trials, search_chembl (2.4M bioactives), and semantic literature search across 14,000 papers.
Contradicting evidence is weighted in and kept in view. The goal is to break a target here, cheaply, rather than in a trial.
Use this when you need to
Confirm a target is worth the compute before committing it
Surface failed trials and contradicting evidence early
Rank competing target hypotheses by weighted evidence
Document why a target advanced or stalled, for the audit trail
Break the weak targets here, not in the clinic.
Five evidence streams, weighted adversarially. The contradicting evidence, surfaced before you spend.