Systematic literature reviews are the scientific backbone of life sciences, providing the evidence-based insights necessary for R&D optimization, market access, and patient safety.
These reviews are resource-intensive. When outsourced, companies might loose granular traceability and the ability to seamlessly update their findings.
Biolevate bridges this gap by enabling teams to scale their literature workflows without compromising control, ensuring full traceability and consistent, repeatable outputs at every step.
16× faster cycles
Shorten systematic literature reviews from weeks to days with automated retrieval, screening, extraction, and synthesis.
9× broader evidence coverage
Scale expert screening/extraction logic across larger corpora (e.g., 180 → 2,000+ papers/year) without adding headcount.
Up to 99% accuracy
Accuracy up to 99% (vs ~83% baseline) with standardized templates, source-linked claims, and full traceability for audit-ready outputs.
How it works
1
Retrieve & filter documents from internal repositories or external sources (PubMed, arXiv, OpenAI-ready corpora). Biolevate automates query expansion and deduplication to build a complete, traceable corpus.
2
Define a screening logic (inclusion/exclusion criteria) on a small sample set. Biolevate then applies this logic at scale across the corpus to produce a curated, auditable selection.
3
Define an extraction logic (fields, tables, outcomes, endpoints). Biolevate extracts structured evidence from each selected article and compiles it into standardized datasets.
4
Generate the synthesis (report, slide-ready summary, evidence tables) using your templates and extracted data. Every claim stays linked to sources with a full run record and audit trail.
Regulatory-grade traceability: every statement is grounded in referenced passages with a complete run record and audit trail.
Reusable evidence base: extracted, structured evidence becomes a living asset for downstream projects (HTA, safety, clinical strategy).