Know which patients will respond, before clinical trials
Trials are populations, not an average patient. NovoMCP returns CYP metabolism profiles, pharmacogenomic population breakdowns, and resistance variant flags in seconds. Catch candidates that fail in specific populations before they advance.
“Which patient populations will respond to this EGFR inhibitor given known CYP2D6 polymorphisms and resistance variants?”
How it works
Submit a candidate and target gene
Provide the SMILES, target gene symbol, and optional ADMET results. The engine cross-references 56 pharmacogene profiles, 135K ClinVar pathogenic variants, and CYP metabolism from upstream ADMET predictions.
Population-level analysis
CYP2D6, CYP2C9, CYP3A4 metabolizer phenotypes by population. Resistance variants affecting the binding site flagged. HGNC gene symbol validation against 44K symbols + 58K aliases.
Clinical viability summary
Which populations will respond, which will metabolize too fast or too slow, where resistance is prevalent. A clear stratification output for clinical planning, synthesized for the decision.
Proof
56 pharmacogene documents. 134,940 ClinVar pathogenic variants. 13,252 with affects_binding_site = true.
HGNC gene symbol validation: 44K symbols + 58K aliases. CYP substrate analysis from ADMET results (CYP3A4, CYP2D6, CYP2C9 substrate probabilities).
Curated omics data indexed for direct query. Results in seconds for any target gene.
Use this when you need to
Identify responder populations before committing to trials
Detect CYP metabolizer risks that could sink a Phase I study
Flag resistance variants that affect binding-site viability
Evaluate clinical viability population by population, past the average
Reduce clinical trial risk with population-level insight
56 pharmacogenes. 135K resistance variants. Stratify before you commit.