Everything you need to know about how Motif can accelerate your biomarker research.
Motif is your AI-powered biomarker discovery and cross-referencing platform powered by 9 specialized AI agents that collaborate to deliver cross-referenced biomarker insights. Each agent handles different aspects: intent analysis, multi-database search across 29+ sources, biomarker extraction using NLP, comprehensive cross-referencing across clinical (ClinVar, CIViC, DGIdb), genomic (gnomAD, dbSNP), pathway (Reactome, Gene Ontology), and regulatory (FDA, Patents) databases, knowledge graph construction, and report generation. Results stream in real-time via WebSocket as they're discovered.
Our AI agents search and cross-reference across 29+ databases including clinical sources (CIViC, DGIdb, ClinVar, PharmGKB, OpenTargets), literature databases (PubMed, PMC, Europe PMC, Semantic Scholar, arXiv, bioRxiv), genomic databases (gnomAD, dbSNP, Ensembl), pathway databases (Reactome, Gene Ontology, STRING-DB), protein databases (UniProt, Human Protein Atlas), regulatory sources (FDA, ClinicalTrials.gov, PatentsView), and chemical databases (ChEMBL, HMDB). Every biomarker receives multi-tier evidence cross-referencing with confidence scoring.
Most queries complete in about 6 minutes. However, processing times may vary depending on query complexity and configurations.
Every biomarker is cross-referenced across 29+ clinical databases including CIViC, DGIdb, ClinVar, PharmGKB, FDA, and ClinicalTrials.gov with multi-tier evidence scoring. Our system provides confidence ratings, clinical context, and direct citations to original research for verification.
Professional-grade outputs include PDF due diligence reports, research evidence summaries, competitive landscape analysis, publication-ready summaries with evidence scores, CSV exports, slide presentations, and grant-ready documentation with full citations.
Yes—Motif features HIPAA compliance, row-level security, production deployment support, real-time streaming architecture, and enterprise-grade multi-level caching. Full PDF processing, figure extraction, and automated full-text analysis are included.
Simply ask specific biomarker questions like "Find sensitivity biomarkers for a combination of gemcitabine and cisplatin in melanoma" or "What mutations predict PD-1 inhibitor resistance in NSCLC?" Our AI agents provide research-backed answers with real-time streaming results. Join the waitlist for early access.