We convert clinical study documents and trial data into submission-ready statistical outputs. From Protocol to SDTM, ADaM, and TLFs—automatically.
> AI: Generating Mapping Specifications...
Mapping 'DOB' -> 'BRTHDTC' (ISO8601)
Annotating eCRF domains (DM, AE, VS, LB)
> AI: Producing SDTM Datasets...
Constructed dm.xpt, ae.xpt, lb.xpt, vs.xpt
> AI: Deriving Analysis Datasets (ADaM)...
Derived ADSL (Safety Flag calculated from Protocol rules)
Derived ADTTE (Time-to-event logic applied)
Today, biostatistics and programming teams manually translate Protocols, CRFs, and SAPs into datasets and reports.
This process relies on repetitive, spec-driven programming and manual QC. It is slow, prone to inconsistency, and carries high submission risk.
"We spend 60% of our time writing specs and mapping variables, and only 40% on actual analysis."
Our product acts as an end-to-end clinical data pipeline engine. Instead of writing code from scratch, teams receive AI-generated specs, datasets, and outputs they can simply review and finalize.
BioParity reads your study documents and generates the full package.
Auto-generates mapping specifications from Protocol/CRF to SDTM, eliminating manual Excel work.
Produces standardized datasets and derivation logic directly from the Analysis Plan.
Automatically annotates Case Report Forms with SDTM variables for submission.
Generates Tables, Listings, and Figures populated with data, ready for the CSR.
BioParity turns study documents + raw data into SDTM/ADaM and TLFs with a full audit trail. Your team stays in control: review every mapping, derivation, and output with traceable evidence.
Upload your study documents and EDC exports. BioParity normalizes formats and identifies study metadata, endpoints, visit schedules, and domain coverage.
The engine drafts SDTM mapping specs and ADaM derivations with field-level evidence. Every rule is linked back to the source section in the Protocol/SAP.
BioParity executes transformations to produce standardized datasets and draft outputs (tables/listings/figures). Outputs come packaged with validation artifacts and traceability metadata.
Review diffs, approve mappings, and export a clean submission-ready package with audit trails. Built-in checks highlight inconsistencies and missing evidence before they become submission risk.
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