Solutions
One intelligence layer, five missions
Healthcare systems, pharma, biotech, clinical research organizations, and CROs all move biomedical documents. They differ in what they need to do with them — so BioMedora exposes the same provenance-carrying pipeline through different workflows.
Healthcare
Give clinical teams longitudinal intelligence without reading twenty charts per patient.
Longitudinal patient intelligence
Cited timelines compile every note, lab, and report into one chronological record — negated and family-history facts correctly excluded.
Chart & referral preparation
Briefings with problems, medications, allergies, abnormal labs, and unresolved issues — each line citing its source sentence.
Medication safety
Reconciliation with knowledge-base interaction review and contradiction detection (allergy vs active medication).
Quality surveillance
Contradictions, stale medication lists, abnormal labs without follow-up — surfaced continuously from the graph.
Pharma
Turn labels, protocols, safety narratives, and literature into queryable structured evidence.
Evidence extraction
Deterministic NLP over drug labels, regulatory documents, and protocols with terminology normalization to RxNorm/ATC.
Drug intelligence
Interaction and contraindication reasoning grounded in the knowledge base with provenance on every edge.
Safety signal workflows
Adverse events extracted, linked to source text, and traceable for pharmacovigilance review.
Governed generative AI
Reasoning contracts forbid unsupported claims; answers carry citations and uncertainty notes suitable for regulated contexts.
Biotech
Make research documents computable without losing their provenance.
Variant intelligence
HGVS notation extraction with gene inference; variants join the graph alongside phenotypes (HPO) and conditions.
Biomarker discovery support
Concept-linked entities across reports enable cross-document cohort queries instead of manual curation.
Knowledge graphs you own
Provenance-carrying relationships exported through controlled APIs into your analysis stack.
Pipeline integration
Idempotent batch APIs fit LIMS and bioinformatics pipelines; results land in your warehouse via transforms.
Clinical Research
Release de-identified data for secondary research — reproducibly.
Research-ready de-identification
Consistent pseudonyms + interval-preserving date shifts make records linkable within a study while protecting identity; residual scans fail closed.
Screening support
Assertion-qualified facts (diagnosed vs ruled out vs family history) reduce chart-review burden in eligibility assessment.
Cohort exploration
Query structured events and timelines rather than raw documents; every answer cites its evidence.
Auditability
Hash-chained audit trails and effective-dated processing make transformations defensible under regulatory scrutiny.
CRO
Automate extraction across sponsors while keeping every tenant isolated.
Multi-format ingestion at volume
PDF, DOCX, HL7 v2, FHIR, C-CDA, CSV normalized uniformly; batches process asynchronously with job observability.
Structured deliverables
Transform APIs map Biomedical IR to your sponsor's schemas (JSON/CSV/timeline/FHIR).
Hard tenant isolation
Sponsor data stays logically separated server-side; API keys scope to service principals per integration.
Transparent commercial meters
Exactly-once usage ledgers make cross-sponsor chargeback straightforward and auditable.
See your workflow on the pipeline
Every workflow above maps to real endpoints. Try them now, or request a walkthrough with your own document types.