Literature evidence is essential to interpret a signature and connect it to a disease mechanism, but the volume of publications makes manual review slow and inconsistent.
Teams need to parse full texts, assess evidence per gene (mechanistic support, causal signal, consensus), then aggregate insights at the signature level to evaluate coherence and actionability.
Producing defensible conclusions requires exhaustive reading, structured scoring, and traceable justifications - difficult to scale across programs with traditional workflows.
10× faster evidence reviews
Automate full-text parsing, per-gene extraction, and scoring to turn days/weeks of manual review into a repeatable workflow.
Exhaustive, consistent scoring
Apply the same evidence criteria across all genes and articles to improve reproducibility and reduce reviewer-to-reviewer variability.
Defensible mechanistic rationale
Generate a traceable evidence pack and signature report that clearly links genes, mechanisms, and disease context to support confident prioritization.
How it works
1
Ingest signature inputs and scope — provide signature data, disease context, up/down regulation hypotheses, and a list of relevant articles (or retrieval criteria) to frame the study.
2
Parse and index full-text literature — Biolevate uploads, parses, and indexes public and proprietary articles to make evidence searchable and traceable at passage level.
3
Run per-gene and signature-level analysis — exhaustively study literature for each gene, compute per‑gene scores (mechanistic support, causal evidence, consensus), then aggregate into signature-level metrics (coherence, actionability).
4
Generate traceable deliverables — produce a per‑gene evidence dossier with justifications and a generic signature report linking the signature to the disease, with source-linked traceability for review and reuse.
Full-text, passage-level traceability: every score and conclusion is linked back to the exact source excerpts.
Per-gene + signature-level scoring: standardized KPIs to quantify evidence strength per gene and roll up to actionable signature insights.