The pipeline before the molecule exists.
Targets, validation, and pharmacogenomic stratification across a curated omics database: 108K target-disease associations, 56 pharmacogenes, 135K resistance variants (shipping as an open SQLite bundle in a future release). Find a target, validate the evidence, and stratify the patients a program will treat and the patients it will spare.
What it looks like in practice.
The accuracy, stated plainly.
associations
indexed
variants
variants
Omics-driven target discovery
A curated layer of target-disease associations, queried by disease. Ranked, traceable to source, and cited in every response.
Validation against the literature
Targets are cross-checked against papers, patents, and clinical trials, so a candidate target arrives with its supporting and contradicting evidence attached.
Resistance, mapped to structure
135K ClinVar pathogenic variants, with the subset that affects the binding site flagged. Resistance is a structural fact, mapped from the first stage.
Pharmacogenomic stratification
Patient stratification across 56 pharmacogenes. The responders and the non-responders a program identifies before it commits to a trial design.
Start the pipeline at the target, with the evidence attached.
NovoMCP is open to a small group of PIs, postdocs, and research engineers. Tell us what you are working on.